Systems and methods for measuring scene information while capturing images using array cameras

Abstract
Systems and methods for measuring scene information while capturing images using array cameras in accordance with embodiments of the invention are disclosed. In one embodiment, a method of measuring scene information while capturing an image using an array camera includes defining at least two subsets of active cameras, configuring the active cameras using image capture settings, capturing image data using the active cameras, synthesizing at least one image using image data captured by a first subset of active cameras, measuring scene information using image data captured by a second subset of active cameras, and determining whether the image capture settings satisfy at least one predetermined criterion for at least one image capture parameter using the measured scene information, where new image capture settings are determined and utilized to configure the active cameras upon a determination that the image capture settings do not satisfy the at least one predetermined criterion.
Description
FIELD OF THE INVENTION

The present invention generally relates to digital cameras and more specifically to systems and methods for evaluating imaging conditions.


BACKGROUND

Current camera technology typically limits image capture possibilities to very specific conditions in which an image of acceptable quality can be produced. As a result of this limitation, several camera settings need to be appropriately chosen before an image of optimal quality can be taken. Cameras have long had the ability to assess the scene conditions and automatically adjust settings such as: exposure time, iris/lens aperture, focus, sensor gain, and the use of neutral density filters. While film-based cameras have traditionally relied on external measuring sensors to select these settings, modern compact digital cameras make use of several through-the-lens measurements that provide image-based data to automatically adjust settings through algorithms that compare these measurements and decide on optimal settings.


The mechanism of exposure provides adjustment of the device sensitivity to the light intensity in the scene. This is in part motivated by the limited dynamic range (ratio of highest to lowest light intensity) of the camera system compared to the dynamic range of intensities in the real world. In an image capture device, a metering and auto-exposure algorithm finds optimal values for the above parameters (some of these parameters may be specified or fixed). An auto-exposure algorithm aims to find the optimal exposure settings for the camera system by modifying a subset of the following parameters: exposure time, iris/lens aperture, sensor gain, and the use of neutral density filters.


Cameras equipped with auto-focus lens can generally capture an image of acceptable quality at a certain focus setting, while relying on an auto-focus algorithm to select the accurate focus position where the chosen parts of the image are considered to be acceptably sharp. In a traditional compact digital camera, auto-focus can be achieved by capturing successive images at varying focus positions through “focus sweep” and selecting the setting corresponding to the image of best “focus”. An auto-focus algorithm aims to find the optimal focus setting for the camera system. The auto-exposure and auto-focus functions in digital cameras share the characteristic that they both generally rely on taking multiple measurements in order to estimate the best camera settings prior to actual image capture.


Auto-exposure algorithms may rely on external light meters/sensors or may evaluate optimal exposure time through the lens by successive image capturing as described above. In many legacy cameras auto-exposure algorithms run concurrently with image preview mode. Due to the fact that preview mode provides real time video, the auto-exposure algorithm is typically configured to make small adjustments in the exposure time since changes in exposure are immediately visible in the preview video. These small adjustments result in delays in identifying optimal exposure times.


Autofocus is another feature that generally runs when the device is in preview mode. Again, since image preview mode provides real time video, the autofocus process typically involves gradually varying the focus point in a slow sweep. Although there are multiple approaches to performing autofocus (including phase detection that uses dedicated focusing sensors), methods appropriate for compact cameras typically involve capturing several images and analyzing the captured images for parameters such as contrast or blur amount. Such autofocus methods, along with slow sweep, can also result in delays.


The High Dynamic Range (HDR) feature provides a means to produce images that convey higher dynamic range (higher ratio of intensities corresponding to light and dark areas in image). In a conventional image capture mode (i.e. one that does not involve capturing HDR information), images are traditionally captured at one exposure level (may vary for each color channel in architectures allowing this). The camera system's dynamic range is typically limited by several factors, including the finite number of bits in the analog-to-digital converters, reduced full-well sensor capacity as well as optical characteristics. HDR mode utilizes a set of methods that sample a scene's dynamic range more aggressively by capturing multiple images of the scene at different exposure levels. Each exposure creates brackets of smaller or regular dynamic range that can be sampled to produce a composite image of high (increased) dynamic range. Various blending models and/or algorithms can be utilized to create a single HDR image from the multiple images. The High Dynamic Range mode typically includes two steps: High Dynamic Range capture and High Dynamic Range Image Blending and Compression. In the High Dynamic Range capture step, multiple images may be captured at a pre-defined difference in exposure setting from the reference exposure; for example, if the reference exposure is EV0, an image with a smaller exposure by a factor of 2 may be captured and an image with a greater exposure by a factor of 2 may be captured as following: EV0, EV−1 (short exposure), EV+1 (long exposure). (Note: numbers follow the exposure value convention and correspond to base-2 logarithmic scale such that EV−1 corresponds to half of EV0 exposure, EV+1 corresponds to double the EV0 exposure).


SUMMARY OF THE INVENTION

Systems and methods for measuring scene information while capturing images using array cameras in accordance with embodiments of the invention are disclosed. In one embodiment, a method of measuring scene information while capturing an image using an array camera includes defining at least two subsets of active cameras, configuring the active cameras using image capture settings for each subset, capturing image data using the active cameras, synthesizing at least one image using image data captured by a first subset of active cameras, measuring scene information using image data captured by a second subset of active cameras, and determining whether the image capture settings satisfy at least one predetermined criterion for at least one image capture parameter using the measured scene information, where new image capture settings are determined and utilized to configure the active cameras upon a determination that the image capture settings do not satisfy the at least one predetermined criterion for at least one image capture parameter.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a block diagram of an array camera in accordance with an embodiment of the invention.



FIG. 2 conceptually illustrates an optic array and an imager array in an array camera module in accordance with an embodiment of the invention.



FIG. 3 is an architecture diagram of an imager array in accordance with an embodiment of the invention.



FIG. 4 is a high level circuit diagram of pixel control and readout circuitry for a plurality of focal planes in an imager array in accordance with an embodiment of the invention.



FIG. 5 conceptually illustrates a layout of color filters and the location of a reference camera in an array camera module in accordance with an embodiment of the invention.



FIG. 6 is a flow chart illustrating a process for capturing image data using subsets of cameras to capture image data and measure scene information in accordance with an embodiment of the invention.



FIG. 7 is a flow chart illustrating a process for determining the image capture settings for cameras within multiple subsets of cameras within an array camera module in accordance with an embodiment of the invention.



FIG. 8 is a chart that conceptually illustrates the manner in which capturing image data with specific image capture settings can result in the capture of a portion of the full dynamic range of a scene.



FIG. 9 is a flow chart illustrating a process for capturing image data using a first subset of cameras in an array camera module for use in synthesizing images while selecting exposure settings using additional image data captured by a second subset of cameras that measure scene information in accordance with an embodiment of the invention.



FIG. 10 is a flow chart illustrating a process for capturing image data using a first subset of cameras in an array camera module for use in synthesizing images while selecting image capture settings for HDR image capture using additional image data captured by a second subset of cameras that measure scene information in accordance with an embodiment of the invention.



FIG. 11 is a flow chart illustrating a process for capturing image data using a first subset of cameras in an array camera module for use in synthesizing images while selecting autofocus parameters using additional image data captured by a second subset of cameras that measure scene information in accordance with an embodiment of the invention.



FIG. 12 is a flow chart illustrating a process for capturing image data using a first subset of cameras in an array camera module for use in synthesizing a video sequence while modifying image capture settings using additional image data captured by a second subset of cameras that measure scene information in accordance with an embodiment of the invention.





DETAILED DISCLOSURE OF THE INVENTION

Turning now to the drawings, systems and methods for measuring scene information while capturing images using array cameras in accordance with embodiments of the invention are illustrated. Array cameras including camera modules that can be utilized to capture image data from different viewpoints are disclosed in U.S. patent application Ser. No. 12/935,504, entitled “Capturing and Processing of Images using Monolithic Camera Array with Heteregeneous Images”, filed May 20, 2009, the disclosure of which is incorporated by reference herein in its entirety. In several embodiments of the invention, two or more subsets of active cameras within an array camera module are defined. Each subset of active cameras is configured using image capture settings specific to either the entire subset or to each individual active camera within the subset. Image data of a scene is captured using the active cameras. In many embodiments, the systems and methods synthesize a high resolution image using image data captured by a first subset of active cameras using a variety of processes including (but not limited to) fusion processes and super-resolution processes. Fusion and super-resolution processes in accordance with embodiments of the invention are disclosed in U.S. patent application Ser. No. 12/967,807, entitled “System and Methods for Synthesizing High Resolution Images Using Super-Resolution Processes”, filed Dec. 14, 2010, the disclosure of which is incorporated by reference herein in its entirety. In further embodiments, scene information is measured using the image data captured by at least a second subset of active cameras. The scene information is used to determine whether the image capture settings satisfy a set of predetermined criteria for parameters including (but not limited to) exposure, focus settings, shutter speed, aperture, and light sensitivity. In several embodiments of the invention, the image capture settings for one subset of active cameras are determined based on image data that includes image data captured by a different subset of active cameras. In further embodiments, the image data captured by any of the active cameras can be utilized to create HDR images. In further embodiments, active cameras are used to measure scene information in parallel and, once the scene information is used to determine image capture settings, active cameras (which may include one or more cameras used to measure scene information) capture image data using the image capture settings and the image data is used to synthesize an image. Systems and methods for measuring scene information while capturing images in accordance with embodiments of the invention are discussed further below.


Array Cameras


Array cameras in accordance with embodiments of the invention can include a camera module and a processor. An array camera in accordance with an embodiment of the invention is illustrated in FIG. 1. The array camera 100 includes a camera module 102 with an array of individual cameras 104 where an array of individual cameras refers to a plurality of cameras in a particular arrangement, such as (but not limited to) the square arrangement utilized in the illustrated embodiment. The camera module 102 is connected to the processor 106 and the processor 106 is connected to a memory 108. Although a specific array camera is illustrated in FIG. 1, any of a variety of different array camera configurations can be utilized in accordance with many different embodiments of the invention.


Array Camera Modules


Camera modules in accordance with embodiments of the invention can be constructed from an imager array and an optic array. A camera module in accordance with an embodiment of the invention is illustrated in FIG. 2. The camera module 200 includes an imager array 230 including an array of focal planes 240 along with a corresponding optic array 210 including an array of lens stacks 220. Within the array of lens stacks, each lens stack 220 creates an optical channel that forms an image of the scene on an array of light sensitive pixels within a corresponding focal plane 240. Each pairing of a lens stack 220 and focal plane 240 forms a single camera 104 within the camera module. Each pixel within a focal plane 240 of a camera 104 generates image data that can be sent from the camera 104 to the processor 108. In many embodiments, the lens stack within each optical channel is configured so that pixels of each focal plane 240 sample the same object space or region within the scene. In several embodiments, the lens stacks are configured so that the pixels that sample the same object space do so with sub-pixel offsets to provide sampling diversity that can be utilized to recover increased resolution through the use of super-resolution processes.


In several embodiments, color filters in individual cameras can be used to pattern the camera module with π filter groups as further discussed in U.S. Provisional Patent Application No. 61/641,165 entitled “Camera Modules Patterned with pi Filter Groups” filed May 1, 2012, the disclosure of which is incorporated by reference herein in its entirety. These cameras can be used to capture data with respect to different colors, or a specific portion of the spectrum. In contrast to applying color filters to the pixels of the camera, color filters in many embodiments of the invention are included in the lens stack. For example, a green color camera can include a lens stack with a green light filter that allows green light to pass through the optical channel. In many embodiments, the pixels in each focal plane are the same and the light information captured by the pixels is differentiated by the color filters in the corresponding lens stack for each filter plane. Although a specific construction of a camera module with an optic array including color filters in the lens stacks is described above, camera modules including π filter groups can be implemented in a variety of ways including (but not limited to) by applying color filters to the pixels of the focal planes of the camera module similar to the manner in which color filters are applied to the pixels of a conventional color camera. In several embodiments, at least one of the cameras in the camera module can include uniform color filters applied to the pixels in its focal plane. In many embodiments, a Bayer filter pattern is applied to the pixels of one of the cameras in a camera module. In a number of embodiments, camera modules are constructed in which color filters are utilized in both the lens stacks and on the pixels of the imager array.


In several embodiments, an array camera generates image data from multiple focal planes and uses a processor to synthesize one or more images of a scene. In certain embodiments, the image data captured by a single focal plane in the sensor array can constitute a low resolution image (the term low resolution here is used only to contrast with higher resolution images), which the processor can use in combination with other low resolution image data captured by the camera module to construct a higher resolution image through Super Resolution processing.


Although specific array cameras are discussed above, many different array cameras are capable of utilizing π filter groups in accordance with embodiments of the invention. Imager arrays in accordance with embodiments of the invention are discussed further below.


Imager Arrays


An imager array in which the image capture settings of a plurality of focal planes can be independently configured in accordance with an embodiment of the invention is illustrated in FIG. 3. The imager array 300 includes a focal plane array core 302 that includes an array of focal planes 304 and all analog signal processing, pixel level control logic, signaling, and analog-to-digital conversion (ADC) circuitry. The imager array also includes focal plane timing and control circuitry 306 that is responsible for controlling the capture of image information using the pixels. In a number of embodiments, the focal plane timing and control circuitry utilizes reset and read-out signals to control the integration time of the pixels. In other embodiments, any of a variety of techniques can be utilized to control integration time of pixels and/or to capture image information using pixels. In many embodiments, the focal plane timing and control circuitry 306 provides flexibility of image information capture control, which enables features including (but not limited to) high dynamic range imaging, high speed video, and electronic image stabilization. In various embodiments, the imager array includes power management and bias generation circuitry 308. The power management and bias generation circuitry 308 provides current and voltage references to analog circuitry such as the reference voltages against which an ADC would measure the signal to be converted against. In many embodiments, the power management and bias circuitry also includes logic that turns off the current/voltage references to certain circuits when they are not in use for power saving reasons. In several embodiments, the imager array includes dark current and fixed pattern (FPN) correction circuitry 310 that increases the consistency of the black level of the image data captured by the imager array and can reduce the appearance of row temporal noise and column fixed pattern noise. In several embodiments, each focal plane includes reference pixels for the purpose of calibrating the dark current and FPN of the focal plane and the control circuitry can keep the reference pixels active when the rest of the pixels of the focal plane are powered down in order to increase the speed with which the imager array can be powered up by reducing the need for calibration of dark current and FPN.


In many embodiments, a single self-contained chip imager includes focal plane framing circuitry 312 that packages the data captured from the focal planes into a container file and can prepare the captured image data for transmission. In several embodiments, the focal plane framing circuitry includes information identifying the focal plane and/or group of pixels from which the captured image data originated. In a number of embodiments, the imager array also includes an interface for transmission of captured image data to external devices. In the illustrated embodiment, the interface is a MIPI CSI 2 output interface (as specified by the non-profit MIPI Alliance, Inc.) supporting four lanes that can support read-out of video at 30 fps from the imager array and incorporating data output interface circuitry 318, interface control circuitry 316 and interface input circuitry 314. Typically, the bandwidth of each lane is optimized for the total number of pixels in the imager array and the desired frame rate. The use of various interfaces including the MIPI CSI 2 interface to transmit image data captured by an array of imagers within an imager array to an external device in accordance with embodiments of the invention is described in U.S. Pat. No. 8,305,456, entitled “Systems and Methods for Transmitting Array Camera Data”, issued Nov. 6, 2012, the disclosure of which is incorporated by reference herein in its entirety.


Although specific components of an imager array architecture are discussed above with respect to FIG. 3, any of a variety of imager arrays can be constructed in accordance with embodiments of the invention that enable the capture of images of a scene at a plurality of focal planes in accordance with embodiments of the invention. Independent focal plane control that can be included in imager arrays in accordance with embodiments of the invention are discussed further below.


Independent Focal Plane Control


Imager arrays in accordance with embodiments of the invention can include an array of focal planes that can independently be controlled. In this way, the image capture settings for each focal plane in an imager array can be configured differently. As is discussed further below, the ability to configure active focal planes using different image capture settings can enable different cameras within an array camera to make independent measurements of scene information that can be combined for use in determining image capture settings for use more generally within the camera array.


An imager array including independent control of image capture settings and independent control of pixel readout in an array of focal planes in accordance with an embodiment of the invention is illustrated in FIG. 4. The imager array 400 includes a plurality of focal planes or pixel sub-arrays 402. Control circuitry 403, 404 provides independent control of the exposure timing and amplification gain applied to the individual pixels within each focal plane. Each focal plane 402 includes independent row timing circuitry 406, 408, and independent column readout circuitry 410, 412. In operation, the control circuitry 403, 404 determines the image capture settings of the pixels in each of the active focal planes 402. The row timing circuitry 406, 408 and the column readout circuitry 410, 412 are responsible for reading out image data from each of the pixels in the active focal planes. The image data read from the focal planes is then formatted for output using an output and control interface 416.


Although specific imager array configurations are discussed above with reference to FIG. 4, any of a variety of imager array configurations including independent and/or related focal plane control can be utilized in accordance with embodiments of the invention including those outlined in U.S. patent application Ser. No. 13/106,797, entitled “Architectures for Imager Arrays and Array Cameras”, filed May 12, 2011, the disclosure of which is incorporated by reference herein in its entirety. The use of independent focal plane control to capture image data using array cameras is discussed further below.


Capturing Image Data with Subsets of Active Cameras


Active cameras in an array camera module in accordance with embodiments of the invention can be grouped into subsets for capturing image data and for measuring scene information. A 4×4 array camera module including a first subset of active cameras that capture image data used to synthesize an image from the viewpoint of a reference camera and a second subset of cameras that capture image data used to obtain (additional) measurements of scene information in accordance with embodiments of the invention is illustrated in FIG. 5. The 4×4 camera module 500 includes a first subset 502 of 3×3 active cameras patterned using a π filter group and utilized to capture image data that can be utilized to synthesize color images and/or video sequences. In the illustrated embodiment, π filter group includes a green camera at each corner, a green reference camera in the center indicated by a box 504, blue cameras above and below the reference camera, and red cameras to the left and rights sides of the reference camera. In several embodiments, the locations of the red and blue cameras within the π filter group are swapped and/or an alternative collection of cameras can be utilized to capture image data to synthesize images. In various embodiments, a second subset 506 of active cameras includes a row of blue, green, and red cameras placed below the π filter group and a column of blue, green, and red cameras placed to the right side of the π filter group with a green camera connecting the row and the column. In various embodiments, the second subset of active cameras is configured to capture image data for measuring scene information as discussed further below. Although all of the cameras in the array camera module illustrated in FIG. 5 are shown as capturing image data, in many embodiments one or more of the cameras within the array camera module can be idle during image capture to conserve power as appropriate to the requirements of a specific application.


Although specific array camera module configurations and partitions of cameras into subsets for synthesizing images and measuring scene information are discussed above with respect to FIG. 5, partitions of active cameras into subsets for the purpose of capturing image data for synthesizing images and for obtaining (additional) measurements of scene information can be utilized with any of a variety of camera module configurations including array camera modules including any number of cameras, array camera modules in which one or more of the cameras capture image data within multiple color channels (i.e. are not monochromatic), and/or array camera modules in which not all cameras of the camera array are active (i.e. not capturing image data or performing measurements) as appropriate to the requirements of a specific application in accordance with embodiments of the invention. Processes for using subsets of active cameras to measure scene information and capture images in accordance with embodiments of the invention are discussed further below.


Measuring Scene Information while Capturing Images


The image capture settings of different subsets of active cameras can be independently configured in accordance with embodiments of the invention. In many embodiments, the image data from a first subset of active cameras can be optionally used to synthesize an image and the image data from a second subset of active cameras can be used to measure scene information. In various embodiments, the image data from any combination of subsets can be used to synthesize images and/or measure scene information. In a number of embodiments, active cameras are used to measure a scene information and a preview image is not generated until image capture settings are determined using the measurements.


A process for using subsets of active cameras to measure scene information and synthesize images in accordance with an embodiment of the invention is illustrated in FIG. 6. The process 600 includes defining (602) two or more subsets of active cameras and configuring the cameras using predetermined image capture settings. In several embodiments, the predetermined image capture settings can be determined based upon specific imaging applications and/or desired image qualities. The active cameras of each subset are set to capture (604) image data utilizing methods including (but not limited) to those discussed above. In many embodiments, the image data captured by the first subset of active cameras is used to optionally synthesize (606) an image using a variety of processes including (but not limited to) fusion processes and super-resolution processes as discussed above. In various embodiments, the image data captured by the second subset of active cameras is used to measure (608) scene information. The measurements of scene information alone or in combination with the image data captured by the first subset of images can be used determine image capture settings that are appropriate for the specific scene imaged by the array camera. In various embodiments, the captured image data that is used to measure scene information can be captured by any combination of multiple cameras. In several embodiments, a determination (610) is made as to whether image capture settings used by any of the cameras in the first or second subsets of cameras satisfy a set of predetermined criteria for parameters including (but not limited to) exposure, focus settings, shutter speed, aperture, and/or light sensitivity. If the image capture setting satisfies the set of predetermined criteria, additional image date can be optionally captured (616). If the image capture settings do not satisfy the set of predetermined criteria, new image capture settings are determined (612) based upon scene information measured by the cameras in the first and/or second subsets of cameras and/or scene information image data captured by the first and/or second subsets of cameras. Using the new image capture settings, the cameras are configured (614) and image data is again captured (604) using the active cameras. In many embodiments, any of a variety of techniques can be utilized to select image capture settings for the cameras in the first and second subsets of cameras. Various processes in accordance with embodiments of the invention for determining image capture settings in accordance with embodiments of the invention based upon measurements of scene information are discussed further below. The process repeats until image capture settings satisfy the predetermined criteria.


Although specific processes for using subsets of active cameras to measure scene information while synthesizing images are discussed above with respect to FIG. 6, any of a variety of processes can be utilized as appropriate to the requirements of a specific application in accordance with embodiments of the invention. Processes for using measured scene information for determining image capture settings are further discussed below.


Determining Image Capture Settings


Image data captured by any subset of active cameras can be used to measure scene information to determine new image capture settings. In many embodiments, the scene information is analyzed to further determine various image capture settings including, but not limited to, exposure, focus settings, shutter speed, aperture, and/or light sensitivity.


A process for determining new image capture settings in accordance with an embodiment of the invention is illustrated in FIG. 7. The process 700 includes determining (702) new image capture settings for cameras in a first subset of active cameras. The new image capture settings are used to configure the first subset of active cameras to capture an additional set of image data used to synthesize an image that can be displayed to a user (e.g. preview mode), and/or saved (e.g. as part of a video sequence). The process also includes determining (704) new image capture settings for cameras in a second subset of active cameras. The new image capture settings for the second subset of active cameras configure the second set of active cameras to capture additional image data in order to measure information concerning the scene. Given that the image data captured by the second set of cameras is not used in synthesizing images, the image capture settings need not be consistent across all cameras and/or across cameras within the same color channel. Indeed, utilizing different image capture settings can be useful in simultaneously sampling the scene using different sets of image capture settings in order to identify a set of image capture settings that satisfies a predetermined set of criteria. In several embodiments, the set of criteria are specified in such a way that use of image capture settings that satisfy the set of criteria when capturing image data used to synthesize an image is likely to yield a predetermined level of image quality within the synthesized image.


Where the cameras in the first subset are utilized to synthesize images used to provide a preview image of the scene and/or to capture images or video of the scene a gradual transition in image capture settings may be preferred. Accordingly, a sweep (full search) across a range of image capture parameters can be performed. In various embodiments, a preview image of the scene can be postponed until the sweep across the range of image capture parameters has reached desired values, where the desired values can be predetermined or be based upon the measurements of scene information. In this way, more cameras can be utilized in parallel to perform the sweep and the sweep can be completed in a shorter amount of time. In several embodiments, the speed of the sweep across a range of image capture settings can be determined based upon the measurements of scene information. In several embodiments, image capture settings of the second subset of cameras is determined to rapidly converge on a set of image capture settings that satisfy a set of predetermined criteria. For example, the range of image capture parameters can be swept at a faster sampling rate by using multiple sets of image capture parameters in parallel. Alternatively, a search can be conducted within the space of image capture that employs a search technique designed to achieve rapid convergence upon a set of image capture settings that satisfy the set of predetermined criteria. With each new set of measurements of scene information obtained with a new set of image capture parameters, the range of image capture settings may be bounded by increasingly narrower bounds and the sweep of image capture settings used to determine the image capture setting for the first subset of cameras is determined to rapidly sweep to the edge of the bounded range of image capture settings. In several embodiments, the number of parallel measurements of scene information is sufficiently large that the process of identifying a set of image capture parameters of the first subset of cameras can be determined using a single set of image capture parameters in a similar manner to that used to determine the image capture settings of cameras in the second subset of cameras. As can readily be appreciated, the specific process used to set the image capture settings of the active cameras in each subset of an array camera module based upon measurements of scene information captured using a first set of image capture settings can be determined using any of a variety of processes as appropriate to the requirements of a specific application in accordance with embodiments of the invention.


Although specific processes for determining image capture settings for two subsets of active cameras are discussed above with respect to FIG. 7, any of a variety of processes can be utilized for determining image capture settings as appropriate to the requirements of a specific application in accordance with embodiments of the invention. Processes for determining image capture setting for utilizing an auto-exposure feature in accordance with embodiments of the invention are further discussed below.


Automatically Determining Exposure Settings


In many auto-exposure algorithms, an image is first captured at a known exposure setting and the captured image is analyzed to determine a more appropriate exposure setting. The iterative process continues until an image is captured that satisfies one or more auto-exposure criteria. In many embodiments, the iterative process can continue until statistics based on image histogram are reached. Such image statistics can include (but not limited to) analyzing histogram distribution, amount of saturated pixels and/or mean pixel values. In several embodiments, the iterative process can continue until a desired number of pixels are underexposed and/or overexposed. In other embodiments, the iterative process can continue until one or more auto-exposure criteria appropriate to the requirements of a specific application are met. As illustrated in FIG. 8, the dynamic range of a scene 802 can be much greater than the dynamic range of the imaging system 806. The difference in dynamic ranges creates a so called clipping effect at the limits of the imaging system's dynamic range 804, 808. The regions of the scene's dynamic range that are outside the imaging system's dynamic range 806 are either underexposed or overexposed and thus image data is not accurately captured. Exposure settings can be adjusted in an iterative approach to identify the exposure setting that best satisfy a set of predetermined criteria and/or to capture image data over the entire dynamic range of the scene for the purposes of HDR imaging. Processes for selecting exposure settings for performing image data capture and for performing HDR image capture in accordance with embodiments of the invention are discussed further below.


A process for determining image capture settings for auto-exposure utilizing two subsets of active cameras within a camera array in accordance with an embodiment of the invention is illustrated in FIG. 9. The process 900 includes capturing (902) image data using the active cameras. In several embodiments, the image data captured by a first subset of active cameras can be used to optionally synthesize an image as discussed above. In many embodiments, the image data captured by the second subset of active cameras are used to measure (904) scene information. In various embodiments, scene information can be measured in parallel to synthesizing images or before synthesizing an image altogether. The measured scene information is used to determine (906) exposure value parameters of the captured image data including (but not limited to) scene luminance intensity and/or scene dynamic range. The process further includes determining (908) whether the image capture settings satisfy a set of predetermined criteria for exposure settings by measuring scene information. In many embodiments, the predetermined criteria can include a particular mean pixel intensity level. In several embodiments, the predetermined criteria can include a particular number of pixels that are underexposed and/or overexposed. In other embodiments, the predetermined criteria can include any number of criteria as appropriate to the requirements of a specific application. If the image capture settings do not satisfy the predetermined criteria for exposure settings then new image capture settings for the active cameras in both the first subset and the second subset can be determined (910) based upon the determined exposure value parameters in accordance with techniques similar to those discussed above. The new image capture settings are used to configure (912) the active cameras and new images data is captured (914). Scene information is measured (904) using the image data captured by at least the second subset of active cameras and the process repeats until image capture settings satisfy predetermined criteria for exposure settings. When the image capture settings satisfy the predetermined criteria for exposure settings, new image capture settings are determined (916) for a set of active cameras and image data is captured (918) using the active cameras. In many embodiments, the active cameras include the first subset of active cameras. In several embodiments, the active cameras can include a different set of active cameras including fewer cameras, more cameras, and/or a subset of cameras including some or all of the first subset of cameras. In many embodiments, the image capture settings are used to capture video with the first subset of cameras. In several embodiments, the image capture settings are used to capture a still image with all of the cameras in the camera array.


Although specific processes for automatically determining image capture settings for auto-exposure using two subsets of active cameras are discussed above with respect to FIG. 9, any of a variety of processes for automatically determining exposure settings can be utilized as appropriate to the requirements of a specific application in accordance with embodiments of the invention. Process for using subsets of active cameras to synthesize HDR images in accordance with embodiments of the invention are further disclosed below.


Automatically Determining HDR Settings


Subset of active cameras can be configured to capture image data in order to determine image capture settings for use in the capture of HDR images. By taking measurements of scene information using different sets of image capture parameters, the image capture settings of various cameras utilized during HDR image capture can be set to capture image data that correspond to various exposure levels within the dynamic range of a scene. In many embodiments, one or more subsets of active cameras capture image data in parallel.


A process for capturing image data at various exposure levels to determine image capture settings for use in the capture of HDR images in accordance with an embodiment of the invention is illustrated in FIG. 10. The process 1000 includes configuring (1002) the image capture settings of a second subset of active cameras to various exposure settings to enable rapid measurement of the dynamic range of the scene. With the image capture settings for the first and second subset of active cameras set to various exposure settings, image data is captured (1004) using the active cameras. In several embodiments, the first and second subsets of active cameras capture image data in parallel. In many embodiments, the captured image data from the second subset of active cameras is used to measure (1006) the dynamic range of the scene. In various embodiments, the image data captured by both the first and second subsets of active cameras can be utilized to measure the scene information. The process of measuring the dynamic range of the scene using different image capture settings continues until a determination (1008) is made that measurement of the dynamic range is complete. The manner in which the settings of the active cameras are modified during the measurement of the dynamic range of the scene can be determined using criteria similar to those discussed above. When the measurement of dynamic range is complete, the process determines image capture settings for HDR image capture and configures (1014) the active cameras at multiple exposure levels that can be utilized to capture (1016) HDR image data. In many embodiments, the exposure bracketing (i.e. differences in exposure settings between subsets of active cameras) can be selected (1009) using the determined dynamic range of the scene. In several embodiments, the exposure bracketing can be predetermined. In other embodiments, the exposure bracketing can be selected depending on predetermined criteria. Such criteria can include (but is not limited to) number of exposure groups available for HDR mode and the difference in scene dynamic range and imaging system's dynamic range. In many embodiments, new image capture settings are determined (1010) and active cameras are then configured (1012) using the new image capture settings to capture image data at each of the exposure settings. As discussed above, the image data at the different exposure settings can then be combined to synthesize HDR images. In some embodiments, the determination that measurement of dynamic range is complete is achieved by comparing the percentage of both under-exposed and over-exposed pixels against pre-determined threshold values. In various embodiments, the auto-exposure and dynamic range determination is not significantly affected by the inherent disparity among the various images of the array. This is because the measurements are based on image histograms which are stable across various views.


In some embodiments, one can use the depth information from the camera array to automatically bracket the exposures to capture HDR. For instance, the depth information from the camera array allows one to determine where the focal plane is (based on the object closest to the camera in the focus window) and the associated depth of field around the focal plane. The exposure for one camera subset can be set to be optimal for the objects in the depth of field, while the exposure for the other subset is set to be optimal for the regions outside the depth of field. In the case of the regions outside the depth of field, there are two of them—the region in front of the in-focus region and the region behind the in-focus region. The exposure for the out-of-focus regions can be set to be optimal either for the region behind the in-focus region or the region in front of the in-focus region or both depending on what is optimal for ensuring the optimal contrast for the in-focus region.


Although specific processes for capturing image data using subsets of active cameras to determine image capture settings at multiple exposure levels that can be utilized to capture HDR image data are discussed above with respect to FIG. 10, any of a variety of processes for determining image capture settings at multiple exposure levels that can be utilized to capture HDR image data based upon measurements of scene information captured by a subset of cameras within a camera array can be utilized as appropriate to the requirements of a specific application in accordance with embodiments of the invention. Processes for using subsets of active cameras to determine autofocus settings are further discussed below.


Automatically Determining Focus Settings


Different image capture settings can be used to configure subsets of active cameras to measure scene information relevant for controlling the focus of optical systems of individual cameras within a camera array. In particular, image data regarding contrast levels among pixels of a single focal plane and relative blur amounts of pixels at various focus settings can be relevant to determining whether image capture settings satisfy predetermined criteria related to focus.


A process for using subsets of active cameras to determine focus settings for optical systems within cameras in a camera array in accordance with an embodiment of the invention is illustrated in FIG. 11. The process 1100 includes capturing (1102) image data using active cameras where the active cameras are defined into a plurality of subsets. In several embodiments, a first subset of cameras is used to capture image data that is used to synthesize an image that can be displayed in a preview mode and/or captured. In many embodiments, automatically determining focus settings can consider spatial correspondences by measuring corresponding image data and/or specific regions of interest within a scene. In various embodiments, this can be achieved by designating at least two individual cameras with the same focus settings such that parallax can be employed for those cameras. This in turn can identify the parallax-induced shift in region of interest in the other cameras compared to the reference camera. In several embodiments, parallax detection and correction can be performed (1103) on each set of cameras sharing focus settings using methods including (but not limited) to techniques disclosed in U.S. Pat. No. 8,619,082, entitled, “Systems and Methods for Parallax Detection and Correction in Images Captured Using Array Cameras that Contain Occlusions Using Subsets of Images to Perform Depth Estimation” filed Aug. 21, 2013, the disclosure of which is incorporated by reference herein in its entirety. In many embodiments, using image data captured by a second subset of active cameras, pixel contrast levels within image data captured using cameras with optical systems configured using specific focal settings can be measured (1104). In a number of embodiments, pixel contrast is also measured using image data captured by the first subset of cameras. In several embodiments, autofocus parameters are determined (1106) using the pixel contrast measurements for the entire image and/or a predefined region of interest. The process further includes determining (1108) whether the image capture settings satisfy predetermined criteria. If the image capture settings do not satisfy the predetermined criteria, then new focus settings are determined (1110) for the active cameras. The focus settings can be determined using techniques similar to those described above and/or in a manner designed to rapidly sample different focus settings in parallel using different cameras within the camera array. The active cameras are configured (1112) using the new focal settings and image data is captured (1114). The process repeats and parallax can be performed (1103) again and pixel contrast with respect to the different focus settings is again measured (1104) and autofocus parameters determined (1106). If focus settings are identified that satisfy the predetermined criteria with respect to autofocus, then identified focus settings are used to configure (1116) a set of active cameras and image data is captured (1118). In many embodiments, the active cameras include the first subset of active cameras. In several embodiments, the active cameras can include a different set of active cameras including fewer cameras, more cameras, and/or a subset of cameras including some or all of the first subset of cameras. In many embodiments, the image capture settings are used to capture video with the first subset of cameras. In several embodiments, the image capture settings are used to capture a still image with all of the cameras in the camera array.


Although specific processes for using subsets of active cameras to measure scene information while capturing video are discussed above with respect to FIG. 11 including processes that involve use of pixel contrast measurements, any of a variety of processes for measuring focus can be utilized as appropriate to the requirements of a specific application in accordance with embodiments of the invention. Processes for using subsets of active cameras to measure scene information during video capture mode are discussed further below.


Measuring Scene Information During Video Capture


Subsets of active cameras can be configured to capture image data to measure scene information during video capture, where the measurements of scene information can be used to adapt in real time the image capture settings of the subset of cameras used to capture image data from which frames of video are synthesized. A process for using subsets of active cameras to measure scene information while capturing image data for video in accordance with an embodiment of the invention is illustrated in FIG. 12. The process 1200 includes defining (1202) two or more subsets of active cameras and configuring the cameras using image capture settings appropriate to each subset. In several embodiments, a first subset of cameras is configured with uniform image capture settings and the cameras in the first subset capture image data that is used to synthesize frames of video. A second subset of cameras can be configured with image capture settings that differ from the image capture settings used to configure the first subset of cameras. In many instances, the image capture settings of cameras within the second subset can differ. In this way multiple measurements of scene information can be performed in parallel and the measurements used to adjust the image capture parameters of the first subset of imagers during the capture of image data used to synthesize subsequent frames of video. Once the image capture settings of the respective subsets have been configured, the active cameras capture (1204) image data.


Image data captured by a first subset of active cameras is used to synthesize (1206) an image. In some embodiments, the captured image data is saved and/or compressed and an image is synthesized in a decoupled manner. The image data captured by a second subset of active cameras can be used to measure (1208) scene information. If the video capture is complete (1210), then the process is complete. If video capture is not complete (1210), new image capture settings are determined (1212) based upon the measured scene information. In many embodiments, the image capture settings of the second subset of cameras are determined relative to the image capture settings determined for the first subset of cameras. In this way, subsequent measurements of scene information are made using image capture settings to which the first subset of cameras can smoothly transition until a stable set of image capture settings are identified. In this way, the aesthetic quality of the video can be enhanced by providing smooth transitions between the image capture settings of the cameras in the first subset of cameras that capture image data used to synthesize successive frames of video. Once the new image capture settings are determined, they can be used to configure (1214) the active cameras. The active cameras again capture (1204) image data and the process repeats until video capture is completed.


In several embodiments, the rate at which the second subset of cameras captures image data differs from the rate at which the first subset of cameras captures image data. In several embodiments, the rate at which the second subset of cameras captures image data can vary depending upon the measured scene information. For example, as parameters such as auto-exposure and/or autofocus stabilize the rate at which image data is captured by the second subset of cameras can be reduced and the rate can be increased in response to detection of such factors including (but not limited to) changes in the measurement of scene information, detection of motion using accelerometers within an array camera, and/or receipt of a user instruction to modify the focal plane of the captured images.


Although specific processes for using subsets of active cameras to measure scene information while capturing video are discussed above with respect to FIG. 12, any of a variety of processes for measuring scene information while capturing video can be utilized as appropriate to the requirements of a specific application in accordance with embodiments of the invention.


While the above description contains many specific embodiments of the invention, these should not be construed as limitations on the scope of the invention, but rather as an example of one embodiment thereof. It is therefore to be understood that the present invention may be practiced otherwise than specifically described, without departing from the scope and spirit of the present invention. Thus, embodiments of the present invention should be considered in all respects as illustrative and not restrictive.

Claims
  • 1. A method of measuring scene information while capturing an image using an array camera, the method comprising: defining a first subset and a second subset of active cameras in an array camera using a processor configured by software, wherein the first subset includes a first active camera, the second subset includes a second active camera different than the first active camera, and the first subset includes more than one active camera;configuring the first subset and the second subset of active cameras in the array camera with image capture settings for each subset using the processor configured by software;capturing image data using the active cameras in the array camera;synthesizing at least one image from image data captured by the first subset of active cameras using the processor configured by software;measuring scene information using the processor configured by software based upon image data captured by the second subset of active cameras, wherein measuring the scene information is performed independently of image data captured by the first subset of active cameras;determining whether the image capture settings satisfy at least one predetermined criterion for at least one image capture parameter based upon the measured scene information obtained using the image data captured by the second subset of active cameras using the processor configured by software; andwhen the image capture settings do not satisfy the at least one predetermined criterion for at least one image capture parameter, determine new image capture settings and configure the first subset of active cameras in the array camera, independently of the second subset of active cameras, with the new image capture settings using the processor configured by software.
  • 2. The method of claim 1, wherein a subset of active cameras is configured using image capture settings specific to the entire subset of active cameras.
  • 3. The method of claim 1, wherein a subset of active cameras is configured using image capture settings specific to each individual active camera within the subset.
  • 4. The method of claim 1, wherein synthesizing at least one image using image data captured by the first subset of active cameras comprises fusing image data captured by the cameras in the first subset of active cameras to create a high resolution image.
  • 5. The method of claim 4, wherein synthesizing at least one image using image data captured by the first subset of active cameras further comprises performing super resolution processing using the image data captured by the cameras in the first subset of active cameras to create a high resolution image.
  • 6. The method of claim 1, wherein the at least one predetermined criterion is at least one predetermined criterion for a parameter selected from the group consisting of exposure, focus settings, shutter speed, aperture, and light sensitivity.
  • 7. The method of claim 1, wherein the cameras in the second subset of active cameras are configured using different image capture settings and measure different scene information in parallel.
  • 8. The method of claim 1, wherein the new image capture settings are used to configure the first subset of active cameras to capture an additional set of image data used to synthesize an image and the new image capture settings for the second subset of active cameras configure the second set of active cameras to capture additional image data in order to measure additional information concerning the scene.
  • 9. The method of claim 8, wherein the new image capture settings for the second subset of active cameras are determined so that the first subset of cameras can smoothly transition to the image capture settings of any camera in the second subset of active cameras.
  • 10. The method of claim 1, wherein the new image capture settings are used to configure a set of active cameras to capture an additional set of image data used to synthesize an image and the set of active cameras is larger than the first subset of active cameras and includes at least one camera from the second subset of cameras.
  • 11. The method of claim 1, wherein: the measured scene information comprises exposure measurements at each of the different image capture settings; andthe at least one predetermined criterion for at least one image capture parameter is at least one predetermined criterion with respect to auto-exposure.
  • 12. The method of claim 1, wherein: the measured scene information comprises measurements of the dynamic range of the scene;the at least one predetermined criterion for at least one image capture parameter comprises determination of image capture settings for high dynamic range image capture based upon measurements of the dynamic range of the scene; andwhen the image capture settings satisfy the at least one predetermined criterion for at least one image capture parameter: configure a plurality of subsets of active cameras using the processor configured by software, where each subset of active cameras has different image capture settings;capture image data using the plurality of active cameras; andsynthesize at least one high dynamic range image from image data captured by the plurality of active cameras using the processor configured by software.
  • 13. The method of claim 1, wherein: cameras in the array camera include autofocus mechanisms;the measured scene information comprises focus measurements at each of the different image capture settings; andthe at least one predetermined criterion for at least one image capture parameter is at least one predetermined criterion with respect to autofocus.
  • 14. The method of claim 1, wherein the first subset of active cameras comprises a 3×3 array of active cameras patterned using a π filter group, where the π filter group includes: a green camera at each corner,a green reference camera in the center,blue cameras on opposite sides of the reference camera, andred cameras on opposite sides of the reference camera.
  • 15. The method of claim 1, wherein the array camera includes a camera module comprising an array of individual cameras.
  • 16. The method of claim 15, wherein the camera module comprises: an imager array including an array of focal planes, where each focal plane comprises an array of light sensitive pixels;an optic array including an array of lens stacks, where each lens stack creates an optical channel that forms an image on the array of light sensitive pixels within a corresponding focal plane;wherein pairings of lens stacks and focal planes form multiple cameras including the plurality of active cameras.
  • 17. The method of claim 16, wherein the lens stacks within the optical channels sample the same object space with sub-pixel offsets to provide sampling diversity.
  • 18. A method of measuring scene information while capturing an image using an array camera, the method comprising: configuring a plurality of active cameras within an array camera with different image capture settings using a processor configured by software, the plurality of active cameras including a first subset and a second subset of active cameras, wherein the first subset includes a first active camera, and the second subset includes a second active camera different than the first active camera;capturing image data using the active cameras in the array camera;measuring scene information using the processor configured by software based upon image data captured by the second subset of active cameras in parallel with the first subset of active cameras using different image capture settings, wherein measuring the scene information is performed independently of image data captured by the first subset of active cameras;determining whether image capture settings satisfy at least one predetermined criterion for at least one image capture parameter based upon the measured scene information obtained using the image data captured by the second subset of active cameras using the processor configured by software;when the image capture settings do not satisfy the at least one predetermined criterion for at least one image capture parameter, determine a first set of new image capture settings and a second set of new image capture settings, configure the first subset of active cameras with the first set of new image capture settings, and configure the second subset of active cameras in the array camera with the second set of new image capture settings to make additional measurements of scene information using the processor configured by software; andwhen the image capture settings satisfy the at least one predetermined criterion for at least one image capture parameter: configure a plurality of active cameras in the array camera using the image capture settings using the processor configured by software;capture image data using the plurality of active cameras; andsynthesize at least one image from image data captured by the plurality of active cameras using the processor configured by software.
  • 19. The method of claim 18, wherein: the measured scene information comprises exposure measurements at each of the different image capture settings; andthe at least one predetermined criterion for at least one image capture parameter is at least one predetermined criterion with respect to auto-exposure.
  • 20. The method of claim 18, wherein: the measured scene information comprises measurements of the dynamic range of the scene;the at least one predetermined criterion for at least one image capture parameter comprises determination of image capture settings for high dynamic range image capture based upon measurements of the dynamic range of the scene;configuring a plurality of active cameras using the image capture settings further comprises configuring a plurality of subsets of active cameras using the processor configured by software, where each subset of active cameras has different image capture settings; andsynthesizing at least one image from image data captured by the plurality of active cameras further comprises synthesizing at least one high dynamic range image from image data captured by the plurality of active cameras using the processor configured by software.
  • 21. The method of claim 18, wherein: cameras in the array camera include autofocus mechanisms;the measured scene information comprises focus measurements at each of the different image capture settings; andthe at least one predetermined criterion for at least one image capture parameter is at least one predetermined criterion with respect to autofocus.
PCT Information
Filing Document Filing Date Country Kind
PCT/US2014/022118 3/7/2014 WO 00
Publishing Document Publishing Date Country Kind
WO2014/138695 9/12/2014 WO A
US Referenced Citations (938)
Number Name Date Kind
4124798 Thompson Nov 1978 A
4198646 Alexander et al. Apr 1980 A
4323925 Abell et al. Apr 1982 A
4460449 Montalbano Jul 1984 A
4467365 Murayama et al. Aug 1984 A
4652909 Glenn Mar 1987 A
4899060 Lischke Feb 1990 A
5005083 Grage Apr 1991 A
5070414 Tsutsumi Dec 1991 A
5144448 Hornbaker Sep 1992 A
5157499 Oguma et al. Oct 1992 A
5325449 Burt Jun 1994 A
5327125 Iwase et al. Jul 1994 A
5488674 Burt Jan 1996 A
5629524 Stettner et al. May 1997 A
5793900 Nourbakhsh et al. Aug 1998 A
5801919 Griencewic et al. Sep 1998 A
5808350 Jack et al. Sep 1998 A
5832312 Rieger et al. Nov 1998 A
5833507 Woodgate et al. Nov 1998 A
5880691 Fossum et al. Mar 1999 A
5911008 I Jun 1999 A
5933190 Dierickx et al. Aug 1999 A
5973844 Burger Oct 1999 A
6002743 Telymonde Dec 1999 A
6005607 Uomori et al. Dec 1999 A
6034690 Gallery Mar 2000 A
6069351 MacK May 2000 A
6069365 Chow et al. May 2000 A
6097394 Levoy et al. Aug 2000 A
6124974 Burger Sep 2000 A
6130786 Osawa et al. Oct 2000 A
6137100 Fossum et al. Oct 2000 A
6137535 Meyers Oct 2000 A
6141048 Meyers Oct 2000 A
6160909 Melen Dec 2000 A
6163414 Kikuchi et al. Dec 2000 A
6172352 Liu et al. Jan 2001 B1
6175379 Uomori et al. Jan 2001 B1
6205241 Melen Mar 2001 B1
6239909 Hayashi et al. May 2001 B1
6292713 Jouppi et al. Sep 2001 B1
6340994 Margulis et al. Jan 2002 B1
6358862 Ireland et al. Mar 2002 B1
6443579 Myers et al. Sep 2002 B1
6476805 Shum et al. Nov 2002 B1
6477260 Shimomura Nov 2002 B1
6502097 Chan et al. Dec 2002 B1
6525302 Dowski, Jr. et al. Feb 2003 B2
6563537 Kawamura et al. May 2003 B1
6571466 Glenn et al. Jun 2003 B1
6603513 Berezin Aug 2003 B1
6611289 Yu Aug 2003 B1
6627896 Hashimoto et al. Sep 2003 B1
6628330 Lin Sep 2003 B1
6635941 Suda Oct 2003 B2
6639596 Shum et al. Oct 2003 B1
6647142 Beardsley Nov 2003 B1
6657218 Noda Dec 2003 B2
6671399 Berestov Dec 2003 B1
6674892 Melen et al. Jan 2004 B1
6750904 Lambert Jun 2004 B1
6765617 Tangen Jul 2004 B1
6771833 Edgar Aug 2004 B1
6774941 Boisvert et al. Aug 2004 B1
6788338 Dinev Sep 2004 B1
6795253 Shinohara Sep 2004 B2
6801653 Wu et al. Oct 2004 B1
6819328 Moriwaki et al. Nov 2004 B1
6819358 Kagle et al. Nov 2004 B1
6879735 Portniaguine et al. Apr 2005 B1
6897454 Sasaki et al. May 2005 B2
6903770 Kobayashi et al. Jun 2005 B1
6909121 Nishikawa Jun 2005 B2
6927922 George et al. Aug 2005 B2
6958862 Joseph Oct 2005 B1
7015954 Foote et al. Mar 2006 B1
7085409 Sawhney et al. Aug 2006 B2
7161614 Yamashita et al. Jan 2007 B1
7199348 Olsen et al. Apr 2007 B2
7206449 Raskar et al. Apr 2007 B2
7235785 Hornback et al. Jun 2007 B2
7262799 Suda Aug 2007 B2
7292735 Blake et al. Nov 2007 B2
7295697 Satoh Nov 2007 B1
7333651 Kim et al. Feb 2008 B1
7369165 Bosco et al. May 2008 B2
7391572 Jacobowitz et al. Jun 2008 B2
7408725 Sato Aug 2008 B2
7425984 Chen Sep 2008 B2
7430312 Gu Sep 2008 B2
7496293 Shamir et al. Feb 2009 B2
7564019 Olsen Jul 2009 B2
7599547 Sun et al. Oct 2009 B2
7606484 Richards et al. Oct 2009 B1
7620265 Wolff Nov 2009 B1
7633511 Shum et al. Dec 2009 B2
7639435 Chiang et al. Dec 2009 B2
7646549 Zalevsky et al. Jan 2010 B2
7657090 Omatsu et al. Feb 2010 B2
7675080 Boettiger Mar 2010 B2
7675681 Tomikawa et al. Mar 2010 B2
7706634 Schmitt et al. Apr 2010 B2
7723662 Levoy et al. May 2010 B2
7738013 Galambos et al. Jun 2010 B2
7741620 Doering et al. Jun 2010 B2
7782364 Smith Aug 2010 B2
7826153 Hong Nov 2010 B2
7840067 Shen et al. Nov 2010 B2
7912673 Hébert et al. Mar 2011 B2
7965314 Miller et al. Jun 2011 B1
7973834 Yang Jul 2011 B2
7986018 Rennie Jul 2011 B2
7990447 Honda et al. Aug 2011 B2
8000498 Shih et al. Aug 2011 B2
8013904 Tan et al. Sep 2011 B2
8027531 Wilburn et al. Sep 2011 B2
8044994 Vetro et al. Oct 2011 B2
8077245 Adamo et al. Dec 2011 B2
8098297 Crisan et al. Jan 2012 B2
8098304 Pinto et al. Jan 2012 B2
8106949 Tan et al. Jan 2012 B2
8126279 Marcellin et al. Feb 2012 B2
8130120 Kawabata et al. Mar 2012 B2
8131097 Lelescu et al. Mar 2012 B2
8149323 Li Apr 2012 B2
8164629 Zhang Apr 2012 B1
8169486 Corcoran et al. May 2012 B2
8180145 Wu et al. May 2012 B2
8189065 Georgiev et al. May 2012 B2
8189089 Georgiev et al. May 2012 B1
8194296 Compton Jun 2012 B2
8212914 Chiu Jul 2012 B2
8213711 Tam Jul 2012 B2
8231814 Duparre Jul 2012 B2
8242426 Ward et al. Aug 2012 B2
8244027 Takahashi Aug 2012 B2
8244058 Intwala et al. Aug 2012 B1
8254668 Mashitani et al. Aug 2012 B2
8279325 Pitts et al. Oct 2012 B2
8280194 Wong et al. Oct 2012 B2
8284240 Saint-Pierre et al. Oct 2012 B2
8289409 Chang Oct 2012 B2
8289440 Pitts et al. Oct 2012 B2
8290358 Georgiev Oct 2012 B1
8294099 Blackwell, Jr. Oct 2012 B2
8294754 Jung et al. Oct 2012 B2
8300085 Yang et al. Oct 2012 B2
8305456 McMahon Nov 2012 B1
8315476 Georgiev et al. Nov 2012 B1
8345144 Georgiev et al. Jan 2013 B1
8360574 Ishak et al. Jan 2013 B2
8400555 Georgiev Mar 2013 B1
8406562 Bassi et al. Mar 2013 B2
8411146 Twede Apr 2013 B2
8446492 Nakano et al. May 2013 B2
8456517 Mor et al. Jun 2013 B2
8493496 Freedman et al. Jul 2013 B2
8514291 Chang et al. Aug 2013 B2
8514491 Duparre Aug 2013 B2
8541730 Inuiya Sep 2013 B2
8542933 Venkataraman et al. Sep 2013 B2
8553093 Wong et al. Oct 2013 B2
8559756 Georgiev et al. Oct 2013 B2
8565547 Strandemar Oct 2013 B2
8576302 Yoshikawa Nov 2013 B2
8577183 Robinson Nov 2013 B2
8581995 Lin et al. Nov 2013 B2
8619082 Ciurea et al. Dec 2013 B1
8648918 Kauker et al. Feb 2014 B2
8655052 Spooner et al. Feb 2014 B2
8682107 Yoon et al. Mar 2014 B2
8687087 Pertsel et al. Apr 2014 B2
8692893 McMahon Apr 2014 B2
8754941 Sarwari et al. Jun 2014 B1
8773536 Zhang Jul 2014 B1
8780113 Ciurea et al. Jul 2014 B1
8804255 Duparre Aug 2014 B2
8830375 Ludwig Sep 2014 B2
8831367 Venkataraman et al. Sep 2014 B2
8836793 Kriesel et al. Sep 2014 B1
8842201 Tajiri Sep 2014 B2
8854462 Herbin et al. Oct 2014 B2
8861089 Duparre Oct 2014 B2
8866912 Mullis Oct 2014 B2
8866920 Venkataraman et al. Oct 2014 B2
8866951 Keelan Oct 2014 B2
8878950 Lelescu et al. Nov 2014 B2
8885059 Venkataraman et al. Nov 2014 B1
8885922 Ito et al. Nov 2014 B2
8896594 Xiong et al. Nov 2014 B2
8896719 Venkataraman et al. Nov 2014 B1
8902321 Venkataraman et al. Dec 2014 B2
8928793 McMahon Jan 2015 B2
8977038 Tian et al. Mar 2015 B2
9001226 Ng et al. Apr 2015 B1
9019426 Han Apr 2015 B2
9025894 Venkataraman et al. May 2015 B2
9025895 Venkataraman et al. May 2015 B2
9030528 Shpunt et al. May 2015 B2
9031335 Venkataraman et al. May 2015 B2
9031342 Venkataraman et al. May 2015 B2
9031343 Venkataraman et al. May 2015 B2
9036928 Venkataraman et al. May 2015 B2
9036931 Venkataraman et al. May 2015 B2
9041823 Venkataraman et al. May 2015 B2
9041824 Lelescu et al. May 2015 B2
9041829 Venkataraman et al. May 2015 B2
9042667 Venkataraman et al. May 2015 B2
9049367 Venkataraman et al. Jun 2015 B2
9055233 Mullis et al. Jun 2015 B2
9060124 Mullis et al. Jun 2015 B2
9077893 Venkataraman et al. Jul 2015 B2
9094661 Venkataraman et al. Jul 2015 B2
9100635 Duparre et al. Aug 2015 B2
9123117 Ciurea et al. Sep 2015 B2
9123118 Ciurea et al. Sep 2015 B2
9124815 Venkataraman et al. Sep 2015 B2
9124831 Mullis Sep 2015 B2
9124864 Mullis Sep 2015 B2
9128228 Duparre Sep 2015 B2
9129183 Venkataraman et al. Sep 2015 B2
9129377 Ciurea et al. Sep 2015 B2
9143711 McMahon Sep 2015 B2
9147254 Ciurea et al. Sep 2015 B2
9185276 Roda et al. Nov 2015 B2
9188765 Venkataraman et al. Nov 2015 B2
9191580 Venkataraman et al. Nov 2015 B2
9197821 McMahon Nov 2015 B2
9210392 Nisenzon et al. Dec 2015 B2
9214013 Venkataraman et al. Dec 2015 B2
9235898 Venkataraman et al. Jan 2016 B2
9235900 Ciurea et al. Jan 2016 B2
9240049 Ciurea et al. Jan 2016 B2
9253380 Venkataraman et al. Feb 2016 B2
9256974 Hines Feb 2016 B1
9264592 Rodda et al. Feb 2016 B2
9264610 Duparre Feb 2016 B2
9361662 Lelescu et al. Jun 2016 B2
9412206 McMahon et al. Aug 2016 B2
9413953 Maeda Aug 2016 B2
9426343 Rodda et al. Aug 2016 B2
9426361 Venkataraman et al. Aug 2016 B2
9438888 Venkataraman et al. Sep 2016 B2
9445003 Lelescu et al. Sep 2016 B1
9456134 Venkataraman et al. Sep 2016 B2
9456196 Kim et al. Sep 2016 B2
9462164 Venkataraman et al. Oct 2016 B2
9485496 Venkataraman et al. Nov 2016 B2
9497370 Venkataraman et al. Nov 2016 B2
9497429 Mullis et al. Nov 2016 B2
9512319 Chatron-Michaud et al. Dec 2016 B2
9516222 Duparre et al. Dec 2016 B2
9519972 Venkataraman et al. Dec 2016 B2
9521319 Rodda et al. Dec 2016 B2
9521416 McMahon et al. Dec 2016 B1
9536166 Venkataraman et al. Jan 2017 B2
9576369 Venkataraman et al. Feb 2017 B2
9578237 Duparre et al. Feb 2017 B2
9578259 Molina Feb 2017 B2
9602805 Venkataraman et al. Mar 2017 B2
9635274 Lin et al. Apr 2017 B2
9638883 Duparre May 2017 B1
9661310 Deng et al. May 2017 B2
9706132 Nisenzon et al. Jul 2017 B2
9712759 Venkataraman et al. Jul 2017 B2
9733486 Lelescu et al. Aug 2017 B2
9749547 Venkataraman et al. Aug 2017 B2
9749568 McMahon Aug 2017 B2
9754422 McMahon et al. Sep 2017 B2
9769365 Jannard Sep 2017 B1
9774831 Venkataraman et al. Sep 2017 B2
9794476 Nayar et al. Oct 2017 B2
9807382 Duparre et al. Oct 2017 B2
9811753 Venkataraman et al. Nov 2017 B2
9813616 Lelescu et al. Nov 2017 B2
20010005225 Clark et al. Jun 2001 A1
20010019621 Hanna et al. Sep 2001 A1
20010028038 Hamaguchi et al. Oct 2001 A1
20010038387 Tomooka et al. Nov 2001 A1
20020012056 Trevino Jan 2002 A1
20020015536 Warren Feb 2002 A1
20020027608 Johnson Mar 2002 A1
20020028014 Ono et al. Mar 2002 A1
20020039438 Mori et al. Apr 2002 A1
20020057845 Fossum May 2002 A1
20020061131 Sawhney et al. May 2002 A1
20020063807 Margulis May 2002 A1
20020075450 Aratani Jun 2002 A1
20020087403 Meyers et al. Jul 2002 A1
20020089596 Yasuo Jul 2002 A1
20020094027 Sato et al. Jul 2002 A1
20020101528 Lee Aug 2002 A1
20020113867 Takigawa et al. Aug 2002 A1
20020113888 Sonoda et al. Aug 2002 A1
20020120634 Min et al. Aug 2002 A1
20020122113 Foote et al. Sep 2002 A1
20020163054 Suda et al. Nov 2002 A1
20020167537 Trajkovic Nov 2002 A1
20020177054 Saitoh et al. Nov 2002 A1
20020190991 Efran et al. Dec 2002 A1
20020195548 Dowski, Jr. et al. Dec 2002 A1
20030025227 Daniell Feb 2003 A1
20030086079 Barth et al. May 2003 A1
20030124763 Fan et al. Jul 2003 A1
20030140347 Varsa Jul 2003 A1
20030179418 Wengender et al. Sep 2003 A1
20030188659 Merry et al. Oct 2003 A1
20030190072 Adkins et al. Oct 2003 A1
20030198377 Ng et al. Oct 2003 A1
20030211405 Venkataraman Nov 2003 A1
20040003409 Berstis et al. Jan 2004 A1
20040008271 Hagimori et al. Jan 2004 A1
20040012689 Tinnerino Jan 2004 A1
20040027358 Nakao Feb 2004 A1
20040047274 Amanai Mar 2004 A1
20040050104 Ghosh et al. Mar 2004 A1
20040056966 Schechner et al. Mar 2004 A1
20040061787 Liu et al. Apr 2004 A1
20040066454 Otani et al. Apr 2004 A1
20040071367 Irani et al. Apr 2004 A1
20040075654 Hsiao et al. Apr 2004 A1
20040096119 Williams May 2004 A1
20040100570 Shizukuishi May 2004 A1
20040105021 Hu et al. Jun 2004 A1
20040114807 Lelescu et al. Jun 2004 A1
20040141659 Zhang et al. Jul 2004 A1
20040151401 Sawhney et al. Aug 2004 A1
20040165090 Ning Aug 2004 A1
20040169617 Yelton et al. Sep 2004 A1
20040170340 Tipping et al. Sep 2004 A1
20040174439 Upton Sep 2004 A1
20040179008 Gordon et al. Sep 2004 A1
20040179834 Szajewski Sep 2004 A1
20040196379 Chen et al. Oct 2004 A1
20040207836 Chhibber et al. Oct 2004 A1
20040213449 Safaee-Rad et al. Oct 2004 A1
20040218809 Blake et al. Nov 2004 A1
20040234873 Venkataraman Nov 2004 A1
20040239885 Jaynes et al. Dec 2004 A1
20040240052 Minefuji et al. Dec 2004 A1
20040251509 Choi Dec 2004 A1
20040264806 Herley Dec 2004 A1
20050006477 Patel Jan 2005 A1
20050007461 Chou et al. Jan 2005 A1
20050009313 Suzuki et al. Jan 2005 A1
20050010621 Pinto et al. Jan 2005 A1
20050012035 Miller Jan 2005 A1
20050036778 DeMonte Feb 2005 A1
20050047678 Jones et al. Mar 2005 A1
20050048690 Yamamoto Mar 2005 A1
20050068436 Fraenkel et al. Mar 2005 A1
20050128509 Tokkonen et al. Jun 2005 A1
20050128595 Shimizu Jun 2005 A1
20050132098 Sonoda et al. Jun 2005 A1
20050134698 Schroeder Jun 2005 A1
20050134699 Nagashima Jun 2005 A1
20050134712 Gruhlke et al. Jun 2005 A1
20050147277 Higaki et al. Jul 2005 A1
20050151759 Gonzalez-Banos et al. Jul 2005 A1
20050168924 Wu et al. Aug 2005 A1
20050175257 Kuroki Aug 2005 A1
20050185711 Pfister et al. Aug 2005 A1
20050205785 Hornback et al. Sep 2005 A1
20050219264 Shum et al. Oct 2005 A1
20050219363 Kohler Oct 2005 A1
20050224843 Boemler Oct 2005 A1
20050225654 Feldman et al. Oct 2005 A1
20050265633 Piacentino Dec 2005 A1
20050275946 Choo et al. Dec 2005 A1
20050286612 Takanashi Dec 2005 A1
20050286756 Hong et al. Dec 2005 A1
20060002635 Nestares et al. Jan 2006 A1
20060007331 Izumi et al. Jan 2006 A1
20060018509 Miyoshi Jan 2006 A1
20060023197 Joel Feb 2006 A1
20060023314 Boettiger et al. Feb 2006 A1
20060028476 Sobel et al. Feb 2006 A1
20060029270 Berestov et al. Feb 2006 A1
20060029271 Miyoshi et al. Feb 2006 A1
20060033005 Jerdev et al. Feb 2006 A1
20060034003 Zalevsky Feb 2006 A1
20060034531 Poon et al. Feb 2006 A1
20060035415 Wood Feb 2006 A1
20060038891 Okutomi et al. Feb 2006 A1
20060039611 Rother Feb 2006 A1
20060046204 Ono et al. Mar 2006 A1
20060049930 Zruya et al. Mar 2006 A1
20060054780 Garrood et al. Mar 2006 A1
20060054782 Olsen et al. Mar 2006 A1
20060055811 Frtiz et al. Mar 2006 A1
20060069478 Iwama Mar 2006 A1
20060072029 Miyatake et al. Apr 2006 A1
20060087747 Ohzawa et al. Apr 2006 A1
20060098888 Morishita May 2006 A1
20060103754 Wenstrand et al. May 2006 A1
20060125936 Gruhike et al. Jun 2006 A1
20060138322 Costello et al. Jun 2006 A1
20060152803 Provitola Jul 2006 A1
20060157640 Perlman et al. Jul 2006 A1
20060159369 Young Jul 2006 A1
20060176566 Boettiger et al. Aug 2006 A1
20060187338 May et al. Aug 2006 A1
20060197937 Bamji et al. Sep 2006 A1
20060203100 Ajito et al. Sep 2006 A1
20060203113 Wada et al. Sep 2006 A1
20060210146 Gu Sep 2006 A1
20060210186 Berkner Sep 2006 A1
20060214085 Olsen Sep 2006 A1
20060221250 Rossbach et al. Oct 2006 A1
20060239549 Kelly et al. Oct 2006 A1
20060243889 Farnworth et al. Nov 2006 A1
20060251410 Trutna Nov 2006 A1
20060274174 Tewinkle Dec 2006 A1
20060278948 Yamaguchi et al. Dec 2006 A1
20060279648 Senba et al. Dec 2006 A1
20060289772 Johnson et al. Dec 2006 A1
20070002159 Olsen et al. Jan 2007 A1
20070008575 Yu et al. Jan 2007 A1
20070009150 Suwa Jan 2007 A1
20070024614 Tam Feb 2007 A1
20070030356 Yea et al. Feb 2007 A1
20070035707 Margulis Feb 2007 A1
20070036427 Nakamura et al. Feb 2007 A1
20070040828 Zalevsky et al. Feb 2007 A1
20070040922 McKee et al. Feb 2007 A1
20070041391 Lin et al. Feb 2007 A1
20070052825 Cho Mar 2007 A1
20070083114 Yang et al. Apr 2007 A1
20070085917 Kobayashi Apr 2007 A1
20070092245 Bazakos et al. Apr 2007 A1
20070102622 Olsen et al. May 2007 A1
20070126898 Feldman Jun 2007 A1
20070127831 Venkataraman Jun 2007 A1
20070139333 Sato et al. Jun 2007 A1
20070140685 Wu et al. Jun 2007 A1
20070146503 Shiraki Jun 2007 A1
20070146511 Kinoshita et al. Jun 2007 A1
20070153335 Hosaka Jul 2007 A1
20070158427 Zhu et al. Jul 2007 A1
20070159541 Sparks et al. Jul 2007 A1
20070160310 Tanida et al. Jul 2007 A1
20070165931 Higaki Jul 2007 A1
20070171290 Kroger Jul 2007 A1
20070177004 Kolehmainen et al. Aug 2007 A1
20070182843 Shimamura et al. Aug 2007 A1
20070201859 Sarrat et al. Aug 2007 A1
20070206241 Smith et al. Sep 2007 A1
20070211164 Olsen et al. Sep 2007 A1
20070216765 Wong et al. Sep 2007 A1
20070225600 Weibrecht et al. Sep 2007 A1
20070228256 Mentzer Oct 2007 A1
20070236595 Pan et al. Oct 2007 A1
20070247517 Zhang et al. Oct 2007 A1
20070257184 Olsen et al. Nov 2007 A1
20070258006 Olsen et al. Nov 2007 A1
20070258706 Raskar et al. Nov 2007 A1
20070263113 Baek et al. Nov 2007 A1
20070263114 Gurevich et al. Nov 2007 A1
20070268374 Robinson Nov 2007 A1
20070296832 Ota et al. Dec 2007 A1
20070296835 Olsen Dec 2007 A1
20070296847 Chang et al. Dec 2007 A1
20070297696 Hamza Dec 2007 A1
20080006859 Mionetto et al. Jan 2008 A1
20080019611 Larkin Jan 2008 A1
20080024683 Damera-Venkata et al. Jan 2008 A1
20080025649 Liu et al. Jan 2008 A1
20080030592 Border et al. Feb 2008 A1
20080030597 Olsen et al. Feb 2008 A1
20080043095 Vetro et al. Feb 2008 A1
20080043096 Vetro et al. Feb 2008 A1
20080054518 Ra et al. Mar 2008 A1
20080056302 Erdal et al. Mar 2008 A1
20080062164 Bassi et al. Mar 2008 A1
20080079805 Takagi et al. Apr 2008 A1
20080080028 Bakin et al. Apr 2008 A1
20080084486 Enge et al. Apr 2008 A1
20080088793 Sverdrup et al. Apr 2008 A1
20080095523 Schilling-Benz Apr 2008 A1
20080099804 Venezia et al. May 2008 A1
20080106620 Sawachi et al. May 2008 A1
20080112059 Choi et al. May 2008 A1
20080112635 Kondo et al. May 2008 A1
20080118241 Tekolste et al. May 2008 A1
20080131019 Ng Jun 2008 A1
20080131107 Ueno Jun 2008 A1
20080151097 Chen et al. Jun 2008 A1
20080152215 Horie et al. Jun 2008 A1
20080152296 Oh et al. Jun 2008 A1
20080156991 Hu et al. Jul 2008 A1
20080158259 Kempf et al. Jul 2008 A1
20080158375 Kakkori et al. Jul 2008 A1
20080158698 Chang et al. Jul 2008 A1
20080165257 Boettiger et al. Jul 2008 A1
20080174670 Olsen et al. Jul 2008 A1
20080187305 Raskar et al. Aug 2008 A1
20080193026 Horie et al. Aug 2008 A1
20080211737 Kim et al. Sep 2008 A1
20080218610 Chapman et al. Sep 2008 A1
20080218611 Parulski et al. Sep 2008 A1
20080218612 Border et al. Sep 2008 A1
20080218613 Janson et al. Sep 2008 A1
20080219654 Border Sep 2008 A1
20080239116 Smith Oct 2008 A1
20080240598 Hasegawa Oct 2008 A1
20080247638 Tanida et al. Oct 2008 A1
20080247653 Moussavi et al. Oct 2008 A1
20080272416 Yun Nov 2008 A1
20080273751 Yuan et al. Nov 2008 A1
20080278591 Barna et al. Nov 2008 A1
20080278610 Boettiger et al. Nov 2008 A1
20080284880 Numata Nov 2008 A1
20080291295 Kato et al. Nov 2008 A1
20080298674 Baker et al. Dec 2008 A1
20080310501 Ward et al. Dec 2008 A1
20090027543 Kanehiro et al. Jan 2009 A1
20090050946 Duparre et al. Feb 2009 A1
20090052743 Techmer Feb 2009 A1
20090060281 Tanida et al. Mar 2009 A1
20090086074 Li Apr 2009 A1
20090091645 Trimeche et al. Apr 2009 A1
20090091806 Inuiya Apr 2009 A1
20090096050 Park Apr 2009 A1
20090102956 Georgiev Apr 2009 A1
20090109306 Shan et al. Apr 2009 A1
20090127430 Hirasawa et al. May 2009 A1
20090128644 Camp, Jr. et al. May 2009 A1
20090128833 Yahav May 2009 A1
20090129667 Ho et al. May 2009 A1
20090140131 Utagawa et al. Jun 2009 A1
20090141933 Wagg Jun 2009 A1
20090147919 Goto et al. Jun 2009 A1
20090152664 Klem et al. Jun 2009 A1
20090167922 Perlman et al. Jul 2009 A1
20090167934 Gupta Jul 2009 A1
20090179142 Duparre et al. Jul 2009 A1
20090180021 Kikuchi et al. Jul 2009 A1
20090200622 Tai et al. Aug 2009 A1
20090201371 Matsuda et al. Aug 2009 A1
20090207235 Francini et al. Aug 2009 A1
20090219435 Yuan et al. Sep 2009 A1
20090225203 Tanida et al. Sep 2009 A1
20090237520 Kaneko et al. Sep 2009 A1
20090245573 Saptharishi et al. Oct 2009 A1
20090256947 Ciurea et al. Oct 2009 A1
20090263017 Tanbakuchi Oct 2009 A1
20090268192 Koenck et al. Oct 2009 A1
20090268970 Babacan et al. Oct 2009 A1
20090268983 Stone Oct 2009 A1
20090274387 Jin Nov 2009 A1
20090284651 Srinivasan Nov 2009 A1
20090290811 Imai Nov 2009 A1
20090297056 Lelescu et al. Dec 2009 A1
20090302205 Olsen Richard I et al. Dec 2009 A9
20090317061 Jung et al. Dec 2009 A1
20090322876 Lee et al. Dec 2009 A1
20090323195 Hembree et al. Dec 2009 A1
20090323206 Oliver et al. Dec 2009 A1
20090324118 Maslov et al. Dec 2009 A1
20100002126 Wenstrand et al. Jan 2010 A1
20100002313 Duparre et al. Jan 2010 A1
20100002314 Duparre Jan 2010 A1
20100007714 Kim et al. Jan 2010 A1
20100013927 Nixon Jan 2010 A1
20100044815 Chang et al. Feb 2010 A1
20100053342 Hwang Mar 2010 A1
20100053600 Tanida et al. Mar 2010 A1
20100060746 Olsen et al. Mar 2010 A9
20100073463 Momonoi et al. Mar 2010 A1
20100074532 Gordon et al. Mar 2010 A1
20100085425 Tan Apr 2010 A1
20100086227 Sun et al. Apr 2010 A1
20100091389 Henriksen et al. Apr 2010 A1
20100097491 Farina et al. Apr 2010 A1
20100103175 Okutomi et al. Apr 2010 A1
20100103259 Tanida et al. Apr 2010 A1
20100103308 Butterfield et al. Apr 2010 A1
20100111444 Coffman May 2010 A1
20100118127 Nam et al. May 2010 A1
20100128145 Pitts et al. May 2010 A1
20100133230 Henriksen et al. Jun 2010 A1
20100133418 Sargent et al. Jun 2010 A1
20100141802 Knight et al. Jun 2010 A1
20100142828 Chang et al. Jun 2010 A1
20100142839 Lakus-Becker Jun 2010 A1
20100157073 Kondo et al. Jun 2010 A1
20100166410 Chang et al. Jun 2010 A1
20100165152 Lim Jul 2010 A1
20100171866 Brady et al. Jul 2010 A1
20100177411 Hegde et al. Jul 2010 A1
20100182406 Benitez et al. Jul 2010 A1
20100194860 Mentz et al. Aug 2010 A1
20100194901 van Hoorebeke et al. Aug 2010 A1
20100195716 Klein et al. Aug 2010 A1
20100201834 Maruyama et al. Aug 2010 A1
20100202054 Niederer Aug 2010 A1
20100202683 Robinson Aug 2010 A1
20100208100 Olsen et al. Aug 2010 A9
20100220212 Perlman et al. Sep 2010 A1
20100223237 Mishra et al. Sep 2010 A1
20100225740 Jung et al. Sep 2010 A1
20100231285 Boomer et al. Sep 2010 A1
20100238327 Griffith et al. Sep 2010 A1
20100244165 Lake et al. Sep 2010 A1
20100254627 Panahpour Tehrani et al. Oct 2010 A1
20100259610 Petersen et al. Oct 2010 A1
20100265346 Iizuka Oct 2010 A1
20100265381 Yamamoto et al. Oct 2010 A1
20100265385 Knight Oct 2010 A1
20100281070 Chan et al. Nov 2010 A1
20100289941 Ito Nov 2010 A1
20100290483 Park et al. Nov 2010 A1
20100302423 Adams, Jr. et al. Dec 2010 A1
20100309292 Ho et al. Dec 2010 A1
20100309368 Choi et al. Dec 2010 A1
20100321595 Chiu et al. Dec 2010 A1
20100321640 Yeh et al. Dec 2010 A1
20100329556 Mitarai et al. Dec 2010 A1
20110001037 Tewinkle Jan 2011 A1
20110018973 Takayama Jan 2011 A1
20110019048 Raynor et al. Jan 2011 A1
20110019243 Constant, Jr. et al. Jan 2011 A1
20110031381 Tay et al. Feb 2011 A1
20110032370 Ludwig Feb 2011 A1
20110033129 Robinson Feb 2011 A1
20110038536 Gong Feb 2011 A1
20110043661 Podoleanu Feb 2011 A1
20110043665 Ogasahara Feb 2011 A1
20110043668 McKinnon et al. Feb 2011 A1
20110044502 Liu et al. Feb 2011 A1
20110051255 Lee et al. Mar 2011 A1
20110055729 Mason et al. Mar 2011 A1
20110064327 Dagher et al. Mar 2011 A1
20110069189 Venkataraman et al. Mar 2011 A1
20110080487 Venkataraman Apr 2011 A1
20110085028 Samadani et al. Apr 2011 A1
20110090217 Mashitani et al. Apr 2011 A1
20110108708 Olsen et al. May 2011 A1
20110115886 Nguyen et al. May 2011 A1
20110121421 Charbon et al. May 2011 A1
20110122308 Duparre May 2011 A1
20110128393 Tavi et al. Jun 2011 A1
20110128412 Milnes et al. Jun 2011 A1
20110129165 Lim et al. Jun 2011 A1
20110141309 Nagashima et al. Jun 2011 A1
20110142138 Tian et al. Jun 2011 A1
20110149408 Hahgholt et al. Jun 2011 A1
20110149409 Haugholt et al. Jun 2011 A1
20110153248 Gu et al. Jun 2011 A1
20110157321 Nakajima et al. Jun 2011 A1
20110157451 Chang Jun 2011 A1
20110169994 DiFrancesco et al. Jul 2011 A1
20110176020 Chang Jul 2011 A1
20110181797 Galstian et al. Jul 2011 A1
20110193944 Lian et al. Aug 2011 A1
20110200319 Kravitz et al. Aug 2011 A1
20110206291 Kashani et al. Aug 2011 A1
20110207074 Hall-Holt et al. Aug 2011 A1
20110211824 Georgiev et al. Sep 2011 A1
20110221599 Högasten Sep 2011 A1
20110221658 Haddick et al. Sep 2011 A1
20110221939 Jerdev Sep 2011 A1
20110221950 Oostra Sep 2011 A1
20110222757 Yeatman, Jr. et al. Sep 2011 A1
20110228142 Brueckner Sep 2011 A1
20110228144 Tian et al. Sep 2011 A1
20110234841 Akeley et al. Sep 2011 A1
20110241234 Duparre Oct 2011 A1
20110242342 Goma et al. Oct 2011 A1
20110242355 Goma et al. Oct 2011 A1
20110242356 Aleksic et al. Oct 2011 A1
20110243428 Das Gupta et al. Oct 2011 A1
20110255592 Sung et al. Oct 2011 A1
20110255745 Hodder et al. Oct 2011 A1
20110261993 Weiming et al. Oct 2011 A1
20110267264 McCarthy et al. Nov 2011 A1
20110267348 Lin et al. Nov 2011 A1
20110273531 Ito et al. Nov 2011 A1
20110274366 Tardif Nov 2011 A1
20110279705 Kuang et al. Nov 2011 A1
20110279721 Mcmahon Nov 2011 A1
20110285701 Chen et al. Nov 2011 A1
20110285866 Bhrugumalla et al. Nov 2011 A1
20110285910 Bamji et al. Nov 2011 A1
20110292216 Fergus et al. Dec 2011 A1
20110298917 Yanagita Dec 2011 A1
20110300929 Tardif et al. Dec 2011 A1
20110310980 Mathew Dec 2011 A1
20110316968 Taguchi et al. Dec 2011 A1
20110317766 Lim, II et al. Dec 2011 A1
20120012748 Pain et al. Jan 2012 A1
20120014456 Martinez Bauza et al. Jan 2012 A1
20120019530 Baker Jan 2012 A1
20120019700 Gaber Jan 2012 A1
20120023456 Sun et al. Jan 2012 A1
20120026297 Sato Feb 2012 A1
20120026342 Yu et al. Feb 2012 A1
20120026366 Golan et al. Feb 2012 A1
20120026451 Nystrom Feb 2012 A1
20120039525 Tian et al. Feb 2012 A1
20120044249 Mashitani et al. Feb 2012 A1
20120044372 Côtéet al. Feb 2012 A1
20120051624 Ando et al. Mar 2012 A1
20120056982 Katz et al. Mar 2012 A1
20120057040 Park et al. Mar 2012 A1
20120062697 Treado et al. Mar 2012 A1
20120062702 Jiang et al. Mar 2012 A1
20120062756 Tian Mar 2012 A1
20120069235 Imai Mar 2012 A1
20120081519 Goma Apr 2012 A1
20120086803 Malzbender et al. Apr 2012 A1
20120105590 Fukumoto et al. May 2012 A1
20120105691 Waqas et al. May 2012 A1
20120113232 Joblove et al. May 2012 A1
20120113318 Galstian et al. May 2012 A1
20120113413 Miahczylowicz-Wolski et al. May 2012 A1
20120127275 Von Zitzewitz et al. May 2012 A1
20120147139 Li et al. Jun 2012 A1
20120147205 Lelescu et al. Jun 2012 A1
20120153153 Chang et al. Jun 2012 A1
20120154551 Inoue Jun 2012 A1
20120155830 Sasaki et al. Jun 2012 A1
20120163672 McKinnon Jun 2012 A1
20120169433 Mullins Jul 2012 A1
20120170134 Bolis et al. Jul 2012 A1
20120176479 Mayhew et al. Jul 2012 A1
20120176481 Lukk et al. Jul 2012 A1
20120188235 Wu et al. Jul 2012 A1
20120188341 Gunnewiek et al. Jul 2012 A1
20120188389 Lin et al. Jul 2012 A1
20120188420 Black et al. Jul 2012 A1
20120188634 Kubala et al. Jul 2012 A1
20120198677 Duparre Aug 2012 A1
20120200669 Lai Aug 2012 A1
20120200726 Bugnariu Aug 2012 A1
20120200734 Tang Aug 2012 A1
20120206582 DiCarlo et al. Aug 2012 A1
20120219236 Ali et al. Aug 2012 A1
20120224083 Jovanovski et al. Sep 2012 A1
20120229602 Chen et al. Sep 2012 A1
20120229628 Ishiyama et al. Sep 2012 A1
20120237114 Park et al. Sep 2012 A1
20120249550 Akeley et al. Oct 2012 A1
20120249750 Izzat et al. Oct 2012 A1
20120249836 Ali et al. Oct 2012 A1
20120249853 Krolczyk et al. Oct 2012 A1
20120262601 Choi et al. Oct 2012 A1
20120262607 Shimura et al. Oct 2012 A1
20120268574 Gidon et al. Oct 2012 A1
20120274626 Hsieh et al. Nov 2012 A1
20120287291 McMahon et al. Nov 2012 A1
20120290257 Hodge et al. Nov 2012 A1
20120293489 Chen et al. Nov 2012 A1
20120293624 Chen et al. Nov 2012 A1
20120293695 Tanaka Nov 2012 A1
20120307093 Miyoshi Dec 2012 A1
20120307099 Yahata et al. Dec 2012 A1
20120314033 Lee et al. Dec 2012 A1
20120314937 Kim et al. Dec 2012 A1
20120327222 Ng et al. Dec 2012 A1
20130002828 Ding et al. Jan 2013 A1
20130003184 Duparre Jan 2013 A1
20130010073 Do Jan 2013 A1
20130016885 Tsujimoto et al. Jan 2013 A1
20130022111 Chen et al. Jan 2013 A1
20130027580 Olsen et al. Jan 2013 A1
20130033579 Wajs Feb 2013 A1
20130033585 Li et al. Feb 2013 A1
20130038696 Ding et al. Feb 2013 A1
20130050504 Safaee-Rad et al. Feb 2013 A1
20130050526 Keelan Feb 2013 A1
20130057710 McMahon Mar 2013 A1
20130070060 Chatterjee Mar 2013 A1
20130076967 Brunner et al. Mar 2013 A1
20130077859 Stauder et al. Mar 2013 A1
20130077880 Venkataraman et al. Mar 2013 A1
20130077882 Venkataraman et al. Mar 2013 A1
20130083172 Baba Apr 2013 A1
20130088489 Schmeitz et al. Apr 2013 A1
20130088637 Duparre Apr 2013 A1
20130093842 Yahata Apr 2013 A1
20130107061 Kumar et al. May 2013 A1
20130113899 Morohoshi et al. May 2013 A1
20130113939 Strandemar May 2013 A1
20130120605 Georgiev et al. May 2013 A1
20130121559 Hu May 2013 A1
20130128068 Georgiev et al. May 2013 A1
20130128069 Georgiev et al. May 2013 A1
20130128087 Georgiev et al. May 2013 A1
20130128121 Agarwala et al. May 2013 A1
20130147979 McMahon et al. Jun 2013 A1
20130176394 Tian et al. Jul 2013 A1
20130208138 Li Aug 2013 A1
20130215108 McMahon et al. Aug 2013 A1
20130215231 Hiramoto et al. Aug 2013 A1
20130222556 Shimada Aug 2013 A1
20130223759 Nishiyama et al. Aug 2013 A1
20130229540 Farina et al. Sep 2013 A1
20130230237 Schlosser et al. Sep 2013 A1
20130250123 Zhang et al. Sep 2013 A1
20130250150 Malone Sep 2013 A1
20130258067 Zhang et al. Oct 2013 A1
20130259317 Gaddy Oct 2013 A1
20130265459 Duparre et al. Oct 2013 A1
20130274596 Azizian et al. Oct 2013 A1
20130274923 By et al. Oct 2013 A1
20130293760 Nisenzon et al. Nov 2013 A1
20140002674 Duparre et al. Jan 2014 A1
20140002675 Duparre et al. Jan 2014 A1
20140009586 McNamer et al. Jan 2014 A1
20140013273 Ng et al. Jan 2014 A1
20140037137 Broaddus et al. Feb 2014 A1
20140037140 Benhimane et al. Feb 2014 A1
20140043507 Wang et al. Feb 2014 A1
20140076336 Clayton et al. Mar 2014 A1
20140078333 Miao Mar 2014 A1
20140079336 Venkataraman et al. Mar 2014 A1
20140085502 Lin et al. Mar 2014 A1
20140092281 Nisenzon et al. Apr 2014 A1
20140098266 Nayar et al. Apr 2014 A1
20140098267 Tian et al. Apr 2014 A1
20140104490 Hsieh et al. Apr 2014 A1
20140118493 Sali et al. May 2014 A1
20140118584 Lee et al. May 2014 A1
20140132810 McMahon May 2014 A1
20140146132 Bagnato et al. May 2014 A1
20140146201 Knight et al. May 2014 A1
20140176592 Wilburn et al. Jun 2014 A1
20140183334 Wang et al. Jul 2014 A1
20140186045 Poddar et al. Jul 2014 A1
20140192154 Jeong et al. Jul 2014 A1
20140192253 Laroia Jul 2014 A1
20140198188 Izawa Jul 2014 A1
20140204183 Lee et al. Jul 2014 A1
20140218546 McMahon Aug 2014 A1
20140232822 Venkataraman et al. Aug 2014 A1
20140240528 Venkataraman et al. Aug 2014 A1
20140240529 Venkataraman et al. Aug 2014 A1
20140253738 Mullis Sep 2014 A1
20140267243 Venkataraman et al. Sep 2014 A1
20140267286 Duparre Sep 2014 A1
20140267633 Venkataraman et al. Sep 2014 A1
20140267762 Mullis et al. Sep 2014 A1
20140267890 Lelescu et al. Sep 2014 A1
20140285675 Mullis Sep 2014 A1
20140313315 Shoham et al. Oct 2014 A1
20140321712 Ciurea et al. Oct 2014 A1
20140333731 Venkataraman et al. Nov 2014 A1
20140333764 Venkataraman et al. Nov 2014 A1
20140333787 Venkataraman et al. Nov 2014 A1
20140340539 Venkataraman et al. Nov 2014 A1
20140347509 Venkataraman et al. Nov 2014 A1
20140347748 Duparre Nov 2014 A1
20140354773 Venkataraman et al. Dec 2014 A1
20140354843 Venkataraman et al. Dec 2014 A1
20140354844 Venkataraman et al. Dec 2014 A1
20140354853 Venkataraman et al. Dec 2014 A1
20140354854 Venkataraman et al. Dec 2014 A1
20140354855 Venkataraman et al. Dec 2014 A1
20140355870 Venkataraman et al. Dec 2014 A1
20140368662 Venkataraman et al. Dec 2014 A1
20140368683 Venkataraman et al. Dec 2014 A1
20140368684 Venkataraman et al. Dec 2014 A1
20140368685 Venkataraman et al. Dec 2014 A1
20140368686 Duparre Dec 2014 A1
20140369612 Venkataraman et al. Dec 2014 A1
20140369615 Venkataraman et al. Dec 2014 A1
20140376825 Venkataraman et al. Dec 2014 A1
20140376826 Venkataraman et al. Dec 2014 A1
20150002734 Lee Jan 2015 A1
20150003752 Venkataraman et al. Jan 2015 A1
20150003753 Venkataraman et al. Jan 2015 A1
20150009353 Venkataraman et al. Jan 2015 A1
20150009354 Venkataraman et al. Jan 2015 A1
20150009362 Venkataraman et al. Jan 2015 A1
20150015669 Venkataraman et al. Jan 2015 A1
20150035992 Mullis Feb 2015 A1
20150036014 Lelescu et al. Feb 2015 A1
20150036015 Lelescu et al. Feb 2015 A1
20150042766 Ciurea et al. Feb 2015 A1
20150042767 Ciurea et al. Feb 2015 A1
20150042833 Lelescu et al. Feb 2015 A1
20150049915 Ciurea et al. Feb 2015 A1
20150049916 Ciurea et al. Feb 2015 A1
20150049917 Ciurea et al. Feb 2015 A1
20150055884 Venkataraman et al. Feb 2015 A1
20150085174 Shabtay et al. Mar 2015 A1
20150091900 Yang et al. Apr 2015 A1
20150098079 Montgomery et al. Apr 2015 A1
20150104076 Hayasaka Apr 2015 A1
20150104101 Bryant et al. Apr 2015 A1
20150122411 Rodda et al. May 2015 A1
20150124113 Rodda et al. May 2015 A1
20150124151 Rodda et al. May 2015 A1
20150146029 Venkataraman et al. May 2015 A1
20150146030 Venkataraman et al. May 2015 A1
20150199841 Venkataraman et al. Jul 2015 A1
20150243480 Yamada et al. Aug 2015 A1
20150244927 Laroia et al. Aug 2015 A1
20150248744 Hayasaka et al. Sep 2015 A1
20150296137 Duparre et al. Oct 2015 A1
20150312455 Venkataraman et al. Oct 2015 A1
20150326852 Duparre et al. Nov 2015 A1
20150332468 Hayasaka et al. Nov 2015 A1
20150373261 Rodda Dec 2015 A1
20160037097 Duparre Feb 2016 A1
20160044252 Gabriel Feb 2016 A1
20160057332 Ciurea et al. Feb 2016 A1
20160165106 Duparre Jun 2016 A1
20160165134 Lelescu et al. Jun 2016 A1
20160165147 Nisenzon et al. Jun 2016 A1
20160165212 Mullis Jun 2016 A1
20160195733 Lelescu et al. Jul 2016 A1
20160227195 Venkataraman et al. Aug 2016 A1
20160249001 McMahon Aug 2016 A1
20160255333 Nisenzon et al. Sep 2016 A1
20160266284 Duparre et al. Sep 2016 A1
20160267665 Venkataraman et al. Sep 2016 A1
20160267672 Ciurea et al. Sep 2016 A1
20160269626 McMahon Sep 2016 A1
20160269627 McMahon Sep 2016 A1
20160269650 Venkataraman et al. Sep 2016 A1
20160269651 Venkataraman et al. Sep 2016 A1
20160269664 Duparre Sep 2016 A1
20160316140 Nayar et al. Oct 2016 A1
20170006233 Venkataraman et al. Jan 2017 A1
20170048468 Pain et al. Feb 2017 A1
20170053382 Lelescu et al. Feb 2017 A1
20170054901 Venkataraman et al. Feb 2017 A1
20170070672 Rodda et al. Mar 2017 A1
20170085845 Venkataraman et al. Mar 2017 A1
20170094243 Venkataraman et al. Mar 2017 A1
20170099465 Mullis et al. Apr 2017 A1
20170163862 Molina Jun 2017 A1
20170178363 Venkataraman et al. Jun 2017 A1
20170187933 Duparre Jun 2017 A1
20180013945 Ciurea et al. Jan 2018 A1
Foreign Referenced Citations (129)
Number Date Country
1669332 Sep 2005 CN
1839394 Sep 2006 CN
101010619 Aug 2007 CN
101064780 Oct 2007 CN
101102388 Jan 2008 CN
101147392 Mar 2008 CN
101427372 May 2009 CN
101606086 Dec 2009 CN
101883291 Nov 2010 CN
102037717 Apr 2011 CN
102375199 Mar 2012 CN
0677821 Oct 1995 EP
840502 May 1998 EP
1201407 May 2002 EP
1355274 Oct 2003 EP
1734766 Dec 2006 EP
2026563 Feb 2009 EP
2104334 Sep 2009 EP
2244484 Oct 2010 EP
2336816 Jun 2011 EP
2381418 Oct 2011 EP
2482022 Jan 2012 GB
59-025483 Sep 1984 JP
64-037177 Jul 1989 JP
02-285772 Nov 1990 JP
H0715457 Jan 1995 JP
09181913 Jul 1997 JP
11142609 May 1999 JP
11223708 Aug 1999 JP
2000209503 Jul 2000 JP
2001008235 Jan 2001 JP
2001194114 Jul 2001 JP
2001264033 Sep 2001 JP
2001277260 Oct 2001 JP
2001337263 Dec 2001 JP
2002195910 Jul 2002 JP
2002205310 Jul 2002 JP
2002252338 Sep 2002 JP
2003094445 Apr 2003 JP
2003139910 May 2003 JP
2003163938 Jun 2003 JP
2003298920 Oct 2003 JP
2004221585 Aug 2004 JP
2005116022 Apr 2005 JP
2005181460 Jul 2005 JP
2005295381 Oct 2005 JP
2005303694 Oct 2005 JP
2005354124 Dec 2005 JP
2006033228 Feb 2006 JP
2006033493 Feb 2006 JP
2006047944 Feb 2006 JP
2006258930 Sep 2006 JP
2007520107 Jul 2007 JP
2007259136 Oct 2007 JP
2008039852 Feb 2008 JP
2008055908 Mar 2008 JP
2008507874 Mar 2008 JP
2008258885 Oct 2008 JP
2009132010 Jun 2009 JP
2009300268 Dec 2009 JP
2011017764 Jan 2011 JP
2011030184 Feb 2011 JP
2011109484 Jun 2011 JP
2011523538 Aug 2011 JP
2013526801 Jun 2013 JP
2014521117 Aug 2014 JP
1020110097647 Aug 2011 KR
200828994 Jul 2008 TW
200939739 Sep 2009 TW
2005057922 Jun 2005 WO
2006039906 Sep 2006 WO
2007013250 Feb 2007 WO
2007083579 Jul 2007 WO
2007134137 Nov 2007 WO
2008045198 Apr 2008 WO
2008050904 May 2008 WO
2008108271 Sep 2008 WO
2008108926 Sep 2008 WO
2008150817 Dec 2008 WO
2009073950 Jun 2009 WO
2009151903 Dec 2009 WO
2009157273 Dec 2009 WO
2011008443 Jan 2011 WO
2011055655 May 2011 WO
2011063347 May 2011 WO
2011105814 Sep 2011 WO
2011116203 Sep 2011 WO
2011063347 Oct 2011 WO
2011143501 Nov 2011 WO
2012057619 May 2012 WO
2012057620 May 2012 WO
2012057621 May 2012 WO
2012057622 May 2012 WO
2012057623 May 2012 WO
2012057620 Jun 2012 WO
2012074361 Jun 2012 WO
2012078126 Jun 2012 WO
2012082904 Jun 2012 WO
2012155119 Nov 2012 WO
2013003276 Jan 2013 WO
2013043751 Mar 2013 WO
2013043761 Mar 2013 WO
2013049699 Apr 2013 WO
2013055960 Apr 2013 WO
2013119706 Aug 2013 WO
2013126578 Aug 2013 WO
2014052974 Apr 2014 WO
2014032020 May 2014 WO
2014078443 May 2014 WO
2014130849 Aug 2014 WO
2014133974 Sep 2014 WO
2014138695 Sep 2014 WO
2014138697 Sep 2014 WO
2014144157 Sep 2014 WO
2014145856 Sep 2014 WO
2014149403 Sep 2014 WO
2014149902 Sep 2014 WO
2014150856 Sep 2014 WO
2014159721 Oct 2014 WO
2014159779 Oct 2014 WO
2014160142 Oct 2014 WO
2014164550 Oct 2014 WO
2014164909 Oct 2014 WO
2014165244 Oct 2014 WO
2014133974 Apr 2015 WO
2015048694 Apr 2015 WO
2015070105 May 2015 WO
2015074078 May 2015 WO
2015081279 Jun 2015 WO
Non-Patent Literature Citations (250)
Entry
Chen et al., “Interactive deformation of light fields”, In Proceedings of SIGGRAPH I3D 2005, pp. 139-146.
Chen et al., “KNN Matting”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Sep. 2013, vol. 35, No. 9, pp. 2175-2188.
Drouin et al., “Fast Multiple-Baseline Stereo with Occlusion”, Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling, 2005, 8 pgs.
Drouin et al., “Geo-Consistency for Wide Multi-Camera Stereo”, Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005, 8 pgs.
Drouin et al., “Improving Border Localization of Multi-Baseline Stereo Using Border-Cut”, International Journal of Computer Vision, Jul. 2009, vol. 83, Issue 3, 8 pgs.
Duparre et al., “Artificial apposition compound eye fabricated by micro-optics technology”, Applied Optics, Aug. 1, 2004, vol. 43, No. 22, pp. 4303-4310.
Duparre et al., “Artificial compound eye zoom camera”, Bioinspiration & Biomimetics, 2008, vol. 3, pp. 1-6.
Duparre et al., “Artificial compound eyes—different concepts and their application to ultra flat image acquisition sensors”, MOEMS and Miniaturized Systems IV, Proc. SPIE 5346, Jan. 2004, pp. 89-100.
Duparre et al., “Chirped arrays of refractive ellipsoidal microlenses for aberration correction under oblique incidence”, Optics Express, Dec. 26, 2005, vol. 13, No. 26, pp. 10539-10551.
Duparre et al., “Micro-optical artificial compound eyes”, Bioinspiration & Biomimetics, 2006, vol. 1, pp. R1-R16.
Duparre et al., “Microoptical artificial compound eyes—from design to experimental verification of two different concepts”, Proc. of SPIE, Optical Design and Engineering II, vol. 5962, pp. 59622A-1-59622A-12 (2005).
Duparre et al., “Microoptical Artificial Compound Eyes—Two Different Concepts for Compact Imaging Systems”, 11th Microoptics Conference, Oct. 30-Nov. 2, 2005, 2 pgs.
Duparre et al., “Microoptical telescope compound eye”, Optics Express, Feb. 7, 2005, vol. 13, No. 3, pp. 889-903.
Duparre et al., “Micro-optically fabricated artificial apposition compound eye”, Electronic Imaging—Science and Technology, Prod. SPIE 5301, Jan. 2004, pp. 25-33.
Duparre et al., “Novel Optics/Micro-Optics for Miniature Imaging Systems”, Proc. of SPIE, 2006, vol. 6196, pp. 619607-1-619607-15.
Duparre et al., “Theoretical analysis of an artificial superposition compound eye for application in ultra flat digital image acquisition devices”, Optical Systems Design, Proc. SPIE 5249, Sep. 2003, pp. 408-418.
Duparre et al., “Thin compound-eye camera”, Applied Optics, May 20, 2005, vol. 44, No. 15, pp. 2949-2956.
Duparre et al., “Ultra-Thin Camera Based on Artificial Apposistion Compound Eyes”, 10th Microoptics Conference, Sep. 1-3, 2004, 2 pgs.
Fanaswala, “Regularized Super-Resolution of Multi-View Images”, Retrieved on Nov. 10, 2012 (Nov. 10, 2012). Retrieved from the Internet at URL:<http://www.site.uottawa.ca/-edubois/theses/Fanaswala—thesis.pdf>, 163 pgs.
Farrell et al., “Resolution and Light Sensitivity Tradeoff with Pixel Size”, Proceedings of the SPIE Electronic Imaging 2006 Conference, 2006, vol. 6069, 8 pgs.
Farsiu et al., “Advances and Challenges in Super-Resolution”, International Journal of Imaging Systems and Technology, 2004, vol. 14, pp. 47-57.
Farsiu et al., “Fast and Robust Multiframe Super Resolution”, IEEE Transactions on Image Processing, Oct. 2004, vol. 13, No. 10, pp. 1327-1344.
Farsiu et al., “Multiframe Demosaicing and Super-Resolution of Color Images”, IEEE Transactions on Image Processing, Jan 2006, vol. 15, No. 1, pp. 141-159.
Feris et al., “Multi-Flash Stereopsis: Depth Edge Preserving Stereo with Small Baseline Illumination”, IEEE Trans on PAMI, 2006, 31 pgs.
Fife et al., “A 3D Multi-Aperture Image Sensor Architecture”, Custom Integrated Circuits Conference, 2006, CICC '06, IEEE, pp. 281-284.
Fife et al., “A 3MPixel Multi-Aperture Image Sensor with 0.7Mu Pixels in 0.11Mu CMOS”, ISSCC 2008, Session 2, Image Sensors & Technology, 2008, pp. 48-50.
Fischer, et al. , “Optical System Design”, 2nd Edition, SPIE Press, pp. 191-198.
Fischer, et al. , “Optical System Design”, 2nd Edition, SPIE Press, pp. 49-58.
Goldman et al., “Video Object Annotation, Navigation, and Composition”, In Proceedings of UIST 2008, pp. 3-12.
Gortler et al., “The Lumigraph”, In Proceedings of SIGGRAPH 1996, pp. 43-54.
Hacohen et al., “Non-Rigid Dense Correspondence with Applications for Image Enhancement”, ACM Transactions on Graphics, 30, 4, 2011, pp. 70:1-70:10.
Hamilton, “JPEG File Interchange Format, Version 1.02”, Sep. 1, 1992, 9 pgs.
Hardie, “A Fast Image Super-Algorithm Using an Adaptive Wiener Filter”, IEEE Transactions on Image Processing, Dec. 2007, vol. 16, No. 12, pp. 2953-2964.
Hasinoff et al., “Search-and-Replace Editing for Personal Photo Collections”, Computational Photography (ICCP) 2010, pp. 1-8.
Horisaki et al., “Irregular Lens Arrangement Design to Improve Imaging Performance of Compound-Eye Imaging Systems”, Applied Physics Express, 2010, vol. 3, pp. 022501-1-022501-3.
Horisaki et al., “Superposition Imaging for Three-Dimensionally Space-Invariant Point Spread Functions”, Applied Physics Express, 2011, vol. 4, pp. 112501-1-112501-3.
Horn et al., “LightShop: Interactive Light Field Manipulation and Rendering”, In Proceedings of I3D 2007, pp. 121-128.
Isaksen et al., “Dynamically Reparameterized Light Fields”, In Proceedings of SIGGRAPH 2000, pp. 297-306.
Jarabo et al., “Efficient Propagation of Light Field Edits”, In Proceedings of SIACG 2011, pp. 75-80.
Joshi, et al. , “Synthetic Aperture Tracking: Tracking Through Occlusions”, I CCV IEEE 11th International Conference on Computer Vision; Publication [online]. Oct. 2007 [retrieved Jul. 28, 2014]. Retrieved from the Internet: <URL: http:l/ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4409032&isnumber=4408819>; pp. 1-8.
Kang et al., “Handling Occlusions inn Dense Multi-View Stereo”, Computer Vision and Pattern Recognition, 2001, vol. 1, pp. I-103-I-110.
Kitamura et al., “Reconstruction of a high-resolution image on a compound-eye image-capturing system”, Applied Optics, Mar. 10, 2004, vol. 43, No. 8, pp. 1719-1727.
Krishnamurthy et al., “Compression and Transmission of Depth Maps for Image-Based Rendering”, Image Processing, 2001, pp. 828-831.
Kutulakos et al., “Occluding Contour Detection Using Affine Invariants and Purposive Viewpoint Control”, Proc., CVPR 94, 8 pgs. (1994).
Lai et al., “A Large-Scale Hierarchical Multi-View RGB-D Object Dataset”, source and date unknown, 8 pgs.
Lee et al., “Electroactive Polymer Actuator for Lens-Drive Unit in Auto-Focus Compact Camera Module”, ETRI Journal, vol. 31, No. 6, Dec. 2009, pp. 695-702.
Lensvector, “How LensVector Autofocus Works”, printed Nov. 2, 2012 from http://www.lensvector.com/overview.html, 1 pg.
Levin et al., “A Closed Form Solution to Natural Image Matting”, Pattern Analysis and Machine Intelligence, Feb. 2008, vol. 30, 8 pgs.
Levoy, “Light Fields and Computational Imaging”, IEEE Computer Society, Aug. 2006, pp. 46-55.
Levoy et al., “Light Field Rendering”, Proc. ADM SIGGRAPH '96, pp. 1-12.
Li et al., “A Hybrid Camera for Motion Deblurring and Depth Map Super-Resolution”, Jun. 23-28, 2008, IEEE Conference on Computer Vision and Pattern Recognition, 8 pgs. Retrieved from www.eecis.udel.edu/˜jye/lab—research/08/deblur-feng.pdf on Feb. 5, 2014.
Liu et al., “Virtual View Reconstruction Using Temporal Information”, 2012 IEEE International Conference on Multimedia and Expo, 2012, pp. 115-120.
Lo et al., “Stereoscopic 3D Copy & Paste”, ACM Transactions on Graphics, vol. 29, No. 6, Article 147, Dec. 2010, pp. 147:1-147:10.
Merkle, Philipp et al., “Adaptation and optimization of coding algorithms for mobile 3DTV”, Mobile3DTV Project No. 216503, 55 pgs.
Mitra et al., “Light Field Denoising, Light Field Superresolution and Stereo Camera Based Refocussing using a GMM Light Field Patch Prior”, Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on Jun. 16-21, 2012, pp. 22-28.
Moreno-Noguer, Francese et al. , “Active Refocusing of Images and Videos”, ACM SIGGRAPH, 2007, vol. 26, pp. 1-10, [retrieved on Jul. 8, 2015], Retrieved from the Internet <U RL:http://doi.acm.org/10.1145/1276377.1276461 >.
Muehlebach, “Camera Auto Exposure Control for VSLAM Applications”, Studies on Mechatronics, Swiss Federal Institute of Technology Zurich, Autumn Term 2010 course, 67 pgs.
International Search Report and Written Opinion for International Application No. PCT/US13/59991, Search Completed Feb. 6, 2014, dated Feb. 26, 2014, 8 pgs.
International Search Report and Written Opinion for International Application No. PCT/US2011/64921, Report Completed Feb. 25, 2011, dated Mar. 6, 2012, 17 pgs.
International Search Report and Written Opinion for International Application No. PCT/US2013/024987, Search Completed Mar. 27, 2013, dated Apr. 15, 2013, 14 pgs.
International Search Report and Written Opinion for International Application No. PCT/US2013/027146, completed Apr. 2, 2013, 12 pgs.
International Search Report and Written Opinion for International Application No. PCT/US2013/039155, Search completed Jul. 1, 2013, dated Jul. 11, 2013, 11 Pgs.
International Search Report and Written Opinion for International Application No. PCT/US2013/048772, Search Completed Oct. 21, 2013, dated Nov. 8, 2013, 11 pgs.
International Search Report and Written Opinion for International Application No. PCT/US2013/056502, Search Completed Feb. 18, 2014, dated Mar. 19, 2014, 7 pgs.
International Search Report and Written Opinion for International Application No. PCT/US2013/069932, International Filing Date Nov. 13, 2013, Search Completed Mar. 14, 2014, dated Apr. 14, 2014, 12 pgs.
International Search Report and Written Opinion for International Application PCT/US11/36349, dated Aug. 22, 2011, 11 pgs.
International Search Report and Written Opinion for International Application PCT/US13/62720, report completed Mar. 25, 2014, dated Apr. 21, 2014, 9 Pgs.
International Search Report and Written Opinion for International Application PCT/US14/024903 report completed Jun. 12, 2014, dated, Jun. 27, 2014, 13 pgs.
International Search Report and Written Opinion for International Application PCT/US14/17766, report completed May 28, 2014, dated Jun. 18, 2014, 9 Pgs.
International Search Report and Written Opinion for International Application PCT/US14/18084, Report completed May 23, 2014, dated Jun. 10, 2014, 12 pgs.
International Search Report and Written Opinion for International Application PCT/US14/18116, report completed May 13, 2014, dated Jun. 2, 2014, 12 Pgs.
International Search Report and Written Opinion for International Application PCT/US14/22118, report completed Jun. 9, 2014, dated, Jun. 25, 2014, 5 pgs.
International Search Report and Written Opinion for International Application PCT/US14/22774 report completed Jun. 9, 2014, dated Jul. 14, 2014, 6 Pgs.
International Search Report and Written Opinion for International Application PCT/US14/24407, report completed Jun. 11, 2014, dated Jul. 8, 2014, 9 Pgs.
International Search Report and Written Opinion for International Application PCT/US14/25100, report completed Jul. 7, 2014, dated Aug. 7, 2014 5 Pgs.
International Search Report and Written Opinion for International Application PCT/US14/25904 report completed Jun. 10, 2014, dated Jul. 10, 2014, 6 Pgs.
International Search Report and Written Opinion for International Application PCT/US2009/044687, completed Jan. 5, 2010, 13 pgs.
International Search Report and Written Opinion for International Application PCT/US201 0/057661, completed Mar. 9, 2011, 14 pgs.
International Search Report and Written Opinion for International Application PCT/US2012/044014, completed Oct. 12, 2012, 15 pgs.
International Search Report and Written Opinion for International Application PCT/US2012/056151, completed Nov. 14, 2012, 10 pgs.
International Search Report and Written Opinion for International Application PCT/US2012/059813, Report completed Dec. 17, 2012, 8 pgs.
International Search Report and Written Opinion for International Application PCT/US2012/37670, dated Jul. 18, 2012, Report completed Jul. 5, 2012, 9 pgs.
International Search Report and Written Opinion for International Application PCT/US2012/58093, Report completed Nov. 15, 2012, 12 pgs.
International Search Report and Written Opinion for International Application PCT/US2014/022123, report completed Jun. 9, 2014, dated Jun. 25, 2014, 5 pgs.
International Search Report and Written Opinion for International Application PCT/US2014/024947, Report Completed Jul. 8, 2014, dated Aug. 5, 2014, 8 Pgs.
International Search Report and Written Opinion for International Application PCT/US2014/028447, report completed Jun. 30, 2014, dated Jul. 21, 2014, 8 Pgs.
International Search Report and Written Opinion for International Application PCT/US2014/030692, report completed Jul. 28, 2014, dated Aug 27, 2014, 7 Pages.
International Search Report and Written Opinion for International Application PCT/US2014/066229, Search Completed Mar. 6, 2015, dated Mar. 19, 2015, 9 Pgs.
International Search Report and Written Opinion for International Application PCT/US2014/067740, Report Completed Jan. 29, 2015, dated Mar. 3, 2015, 10 pgs.
International Search Report and Written Opinion for International Application PCT/US2014/23762, Report Completed May 30, 2014, dated Jul. 3, 2014, 6 Pgs.
Office Action for U.S. Appl. No. 12/952,106, dated Aug. 16, 2012, 12 pgs.
Baker et al., “Limits on Super-Resolution and How to Break Them”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Sep. 2002, vol. 24, No. 9, pp. 1167-1183.
Bertero et al., “Super-resolution in computational imaging”, Micron, 2003, vol. 34, Issues 6-7, 17 pgs.
Bishop, et al., “Full-Resolution Depth Map Estimation from an Aliased Plenoptic Light Field”, ACCV 2010, Part II, LNCS 6493, pp. 186-200.
Bishop, et al., “Light Field Superresolution”, Retrieved from http://home.eps.hw.ac.uk/˜sz73/ICCP09/LightFieldSuperresolution.pdf, 9 pgs.
Bishop et al., “The Light Field Camera: Extended Depth of Field, Aliasing, and Superresolution”, IEEE Transactions on Pattern Analysis and Machine Intelligence, May 2012, vol. 34, No. 5, pp. 972-986.
Borman, “Topics in Multiframe Superresolution Restoration”, Thesis of Sean Borman, Apr. 2004, 282 pgs.
Borman et al, “Image Sequence Processing”, Source unknown, Oct. 14, 2002, 81 pgs.
Borman et al., “Block-Matching Sub-Pixel Motion Estimation from Noisy, Under-Sampled Frames—An Empirical Performance Evaluation”, Proc SPIE, Dec. 1998, 3653, 10 pgs.
Borman et al., “Image Resampling and Constraint Formulation for Multi-Frame Super-Resolution Restoration”, Proc. SPIE, Jun. 2003, 5016, 12 pgs.
Borman et al., “Linear models for multi-frame super-resolution restoration under non-affine registration and spatially varying PSF”, Proc. SPIE, May 2004, vol. 5299, 12 pgs.
Borman et al., “Nonlinear Prediction Methods for Estimation of Clique Weighting Parameters in NonGaussian Image Models”, Proc. SPIE, 1998. 3459, 9 pgs.
Borman et al., “Simultaneous Multi-Frame MAP Super-Resolution Video Enhancement Using Spatio-Temporal Priors”, Image Processing, 1999, ICIP 99 Proceedings, vol. 3, pp. 469-473.
Borman et al., “Super-Resolution from Image Sequences—A Review”, Circuits & Systems, 1998, pp. 374-378.
Bose et al., “Superresolution and Noise Filtering Using Moving Least Squares”, IEEE Transactions on Image Processing, date unknown, 21 pgs.
Boye et al., “Comparison of Subpixel Image Registration Algorithms”, Proc. of SPIE-IS&T Electronic Imaging, vol. 7246, pp. 72460X-1-72460X-9 (2009).
Bruckner et al., “Artificial compound eye applying hyperacuity”, Optics Express, Dec. 11, 2006, vol. 14, No. 25, pp. 12076-12084.
Bruckner et al., “Driving microoptical imaging systems towards miniature camera applications”, Proc. SPIE, Micro-Optics, 2010, 11 pgs.
Bruckner et al., “Thin wafer-level camera lenses inspired by insect compound eyes”, Optics Express, Nov. 22, 2010, vol. 18, No. 24, pp. 24379-24394.
Capel, “Image Mosaicing and Super-resolution”, [online], Retrieved on Nov. 10, 2012 (Nov. 10, 2012). Retrieved from the Internet at URL:<http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.226.2643&rep=rep1 &type=pdf>, Title pg., abstract, table of contents, pp. 1-263 (269 total pages).
Chan et al., “Extending the Depth of Field in a Compound-Eye Imaging System with Super-Resolution Reconstruction”, Proceedings—International Conference on Pattern Recognition, 2006, vol. 3, pp. 623-626.
Chan et al., “Investigation of Computational Compound-Eye Imaging System with Super-Resolution Reconstruction”, IEEE, ISASSP 2006, pp. 1177-1180.
Chan et al., “Super-resolution reconstruction in a computational compound-eye imaging system”, Multidim Syst Sign Process, 2007, vol. 18, pp. 83-101.
Nayar, “Computational Cameras: Redefining the Image”, IEEE Computer Society, Aug. 2006, pp. 30-38.
Ng, “Digital Light Field Photography”, Thesis, Jul. 2006, 203 pgs.
Ng et al., “Super-Resolution Image Restoration from Blurred Low-Resolution Images”, Journal of Mathematical Imaging and Vision, 2005, vol. 23, pp. 367-378.
Nitta et al., “Image reconstruction for thin observation module by bound optics by using the iterative backprojection method”, Applied Optics, May 1, 2006, vol. 45, No. 13, pp. 2893-2900.
Nomura et al., “Scene Collages and Flexible Camera Arrays”, Proceedings of Eurographics Symposium on Rendering, 2007, 12 pgs.
Park et al., “Super-Resolution Image Reconstruction”, IEEE Signal Processing Magazine, May 2003, pp. 21-36.
Perwass et al., “Single Lens 3D-Camera with Extended Depth-of-Field”, printed from www.raytrix.de, 15 pgs.
Pham et al., “Robust Super-Resolution without Regularization”, Journal of Physics: Conference Series 124, 2008, pp. 1-19.
Philips 3D Solutions, “3D Interface Specifications, White Paper”, Philips 3D Solutions retrieved from www.philips.com/3dsolutions, 29 pgs., Feb. 15, 2008.
Polight, “Designing Imaging Products Using Reflowable Autofocus Lenses”, http://www.polight.no/tunable-polymer-autofocus-lens-html--11.html (Nov. 2, 2012).
Pouydebasquea et al., “Varifocal liquid lenses with integrated actuator, high focusing power and low operating voltage fabricated on 200 mm wafers”, Sensors and Actuators A: Physical, vol. 172, Issue 1, Dec. 2011, pp. 280-286.
Protter et al., “Generalizing the Nonlocal-Means to Super-Resolution Reconstruction”, IEEE Transactions on Image Processing, Jan. 2009, vol. 18, No. 1, pp. 36-51.
Radtke et al., “Laser lithographic fabrication and characterization of a spherical artificial compound eye”, Optics Express, Mar. 19, 2007, vol. 15, No. 6, pp. 3067-3077.
Rander, et al., “Virtualized Reality: Constructing Time-Varying Virtual Worlds From Real World Events”, Proc. of IEEE Visualization '97, Phoenix, Arizona, Oct. 19-24, 1997, pp. 277-283, 552.
Rhemann et al, “Fast Cost-Volume Filtering for Visual Correspondence and Beyond”, IEEE Trans. Pattern Anal. Mach. Intell, 2013, vol. 35, No. 2, pp. 504-511.
Robertson et al., “Dynamic Range Improvement Through Multiple Exposures”, In Proc. of the Int. Conf. on Image Processing, 1999, 5 pgs.
Robertson et al., “Estimation-theoretic approach to dynamic range enhancement using multiple exposures”, Journal of Electronic Imaging, Apr. 2003, vol. 12, No. 2, pp. 219-228.
Roy et al., “Non-Uniform Hierarchical Pyramid Stereo for Large Images”, Computer and Robot Vision, 2007, pp. 208-215.
Sauer et al., “Parallel Computation of Sequential Pixel Updates in Statistical Tomographic Reconstruction”, ICIP 1995, pp. 93-96.
Seitz et al., “Plenoptic Image Editing”, International Journal of Computer Vision 48, 2, pp. 115-129.
Shum et al., “Pop-Up Light Field: An Interactive Image-Based Modeling and Rendering System”, Apr. 2004, ACM Transactions on Graphics, vol. 23, No. 2, pp. 143-162. Retrieved from http://131.107.65.14/en-us/um/people/jiansun/papers/PopupLightField—TOG.pdf on Feb. 5.
Stollberg et al., “The Gabor superlens as an alternative wafer-level camera approach inspired by superposition compound eyes of nocturnal insects”, Optics Express, Aug. 31, 2009, vol. 17, No. 18, pp. 15747-15759.
Sun et al., “Image Super-Resolution Using Gradient Profile Prior”, Source and date unknown, 8 pgs.
Takeda et al., “Super-resolution Without Explicit Subpixel Motion Estimation”, IEEE Transaction on Image Processing, Sep. 2009, vol. 18, No. 9, pp. 1958-1975.
Tallon et al., “Upsampling and Denoising of Depth Maps Via Joint- Segmentation”, 20th European Signal Processing Conference, Aug. 27-31, 2012, 5 pgs.
Tanida et al., “Color imaging with an integrated compound imaging system”, Optics Express, Sep. 8, 2003, vol. 11, No. 18, pp. 2109-2117.
Tanida et al., “Thin observation module by bound optics (TOMBO): concept and experimental verification”, Applied Optics, Apr. 10, 2001, vol. 40, No. 11, pp. 1806-1813.
Taylor, “Virtual camera movement: The way of the future?”, American Cinematographer 77, 9 (Sep.), 93-100 (Sep. 9, 1996).
Vaish et al., “Reconstructing Occluded Surfaces Using Synthetic Apertures: Stereo, Focus and Robust Measures”, Proceeding, CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition—vol. 2, pp. 2331-2338.
Vaish et al., “Synthetic Aperture Focusing Using a Shear-Warp Factorization of the Viewing Transform”, IEEE Workshop on A3DISS, CVPR, 2005, 8 pgs.
Vaish et al., “Using Plane + Parallax for Calibrating Dense Camera Arrays”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2004, 8 pgs.
Veilleux, “CCD Gain Lab: The Theory”, University of Maryland, College Park—Observational Astronomy (ASTR 310), Oct. 19, 2006, pp. 1-5 (online, [retrieved on May 13, 2014]. Retrieved from the Internet <URL: http://www.astro.umd.edu/˜veilleux/ASTR310/fall06/ccd—theory.pdf, 5 pgs.
Vuong et al., “A New Auto Exposure and Auto White-Balance Algorithm to Detect High Dynamic Range Conditions Using CMOS Technology”, Proceedings of the World Congress on Engineering and Computer Science 2008, WCECS 2008, Oct. 22-24, 2008.
Wang, “Calculation of Image Position, Size and Orientation Using First Order Properties”, 10 pgs, (Dec. 29, 2010).
Wetzstein et al., “Computational Plenoptic Imaging”, Computer Graphics Forum, 2011, vol. 30, No. 8, pp. 2397-2426.
Wheeler et al., “Super-Resolution Image Synthesis Using Projections Onto Convex Sets in the Frequency Domain”, Proc. SPIE, 2005, 5674, 12 pgs.
Wikipedia, “Polarizing Filter (Photography)”, http://en.wikipedia.org/wiki/Polarizing—filter—(photography), 1 pg, (Dec. 12, 2012).
Wilburn, “High Performance Imaging Using Arrays of Inexpensive Cameras”, Thesis of Bennett Wilburn, Dec. 2004, 128 pgs.
Wilburn et al., “High Performance Imaging Using Large Camera Arrays”, ACM Transactions on Graphics, Jul. 2005, vol. 24, No. 3, pp. 1-12.
Wilburn et al., “High-Speed Videography Using a Dense Camera Array”, Proceeding, CVPR'04 Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 294-301.
Wilburn et al., “The Light Field Video Camera”, Proceedings of Media Processors 2002, SPIE Electronic Imaging, 2002, 8 pgs.
Wippermann et al., “Design and fabrication of a chirped array of refractive ellipsoidal micro-lenses for an apposition eye camera objective”, Proceedings of SPIE, Optical Design and Engineering II, Oct. 15, 2005, 59622C-1-59622C-11.
Yang et al., “A Real-Time Distributed Light Field Camera”, Eurographics Workshop on Rendering (2002), pp. 1-10.
Yang et al., “Superresolution Using Preconditioned Conjugate Gradient Method”, Source and date unknown, 8 pgs.
Zhang, Qiang et al. , “Depth estimation, spatially variant image registration, and super-resolution using a multi-lenslet camera”, Proceedings of SPIE, vol. 7705, Apr. 23, 2010, pp. 770505-770505-8, XP055113797 ISSN: 0277-786X, DOI: 10.1117/12.852171.
Zhang et al., “A Self-Reconfigurable Camera Array”, Eurographics Symposium on Rendering, 2004, 12 pgs.
Zomet et al., “Robust Super-Resolution”, IEEE, 2001, pp. 1-6.
“International Search Report and Written Opinion for International Application PCT/US2014/064693, Report Completed Mar. 7, 2015, dated Apr. 2, 2015, 15 pgs.”.
Extended European Search Report for European Application EP12782935.6, report completed Aug. 28, 2014 dated Sep. 4, 2014, 6 Pgs.
Extended European Search Report for European Application EP12804266.0, Report Completed Jan. 27, 2015, dated Feb. 3, 2015, 6 Pgs.
Extended European Search Report for European Application EP12835041.0, Report Completed Jan. 28, 2015, dated Feb. 4, 2015, 6 Pgs.
International Preliminary Report on Patentability for International Application No. PCT/US2012/059813, International Filing Date Oct. 11, 2012, Search Completed Apr. 15, 2014, 7 pgs.
International Preliminary Report on Patentability for International Application No. PCT/US2013/059991, Report Issued Mar. 17, 2015, dated Mar. 26, 2015, 8 pgs.
International Preliminary Report on Patentability for International Application PCT/US13/56065, Report Issued Feb. 24, 2015, dated Mar. 5, 2015, 4 Pgs.
International Preliminary Report on Patentability for International Application PCT/US13/62720, Report Issued Mar. 31, 2015, dated Apr. 9, 2015, 8 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2013/024987, dated Aug. 21, 2014, 13 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2013/027146, International Filing Date Feb. 21, 2013, Report Completed Apr. 2, 2013, Report Issued Aug. 26, 2014, 10 pages.
International Preliminary Report on Patentability for International Application PCT/US2013/039155, report completed Nov. 4, 2014, dated Nov. 13, 2014, 10 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2013/046002, Report issued Dec. 31, 2014, dated Jan. 8, 2015, 6 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2013/048772, Report issued Dec. 31, 2014, dated Jan. 8, 2015, 8 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2013/056502, Report Issued Feb. 24, 2015, dated Mar. 5, 2015, 7 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/022118, Report issued Sep. 8, 2015, dated Sep. 17, 2015, 4pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/023762, Report issued Mar. 2, 2015, dated Mar. 9, 2015, 10 Pgs.
International Search Report and Written Opinion for International Application No. PCT/US13/46002, Search completed Nov. 13, 2013, dated Nov. 29, 2013, 7 pgs.
International Search Report and Written Opinion for International Application No. PCT/US13/56065, Search Completed Nov. 25, 2013, dated Nov. 26, 2013, 8 pgs.
Extended European Search Report for EP Application No. 13810429.4, Completed Jan. 7, 2016, dated Jan. 15, 2016, 6 Pgs.
Extended European Search Report for European Application EP13810229.8, Report Completed Apr. 14, 2016, dated Apr. 21, 2016, 7 pgs.
Extended European Search Report for European Application No. 13830945.5, Search completed Jun. 28, 2016, dated Jul. 7, 2016, 14 Pgs.
Extended European Search Report for European Application No. 13841613.6, Search completed Jul. 18, 2016, dated Jul. 26, 2016, 8 Pgs.
Supplementary European Search Report for EP Application No. 13831768.0, Search completed May 18, 2016, dated May 30, 2016, 13 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2013/069932, issued May 19, 2015, dated May 28, 2015, 12 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/017766, issued Aug. 25, 2015, dated Sep. 3, 2015, 8 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/018084, issued Aug. 25, 2015, dated Sep. 3, 2015, 11 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/018116, issued Sep. 15, 2015, dated Sep. 24, 2015, 12 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/021439, issued Sep. 15, 2015, dated Sep. 24, 2015, 9 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/022123, issued Sep. 8, 2015, dated Sep. 17, 2015, 4 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/022774, issued Sep. 22, 2015, dated Oct. 1, 2015, 5 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/024407, issued Sep. 15, 2015, dated Sep. 24, 2015, 8 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/024903, issued Sep. 15, 2015, dated Sep. 24, 2015, 12 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/024947, issued Sep. 15, 2015, dated Sep. 24, 2015, 7 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/025100, issued Sep. 15, 2015, dated Sep. 24, 2015, 4 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/025904, issued Sep. 15, 2015, dated Sep. 24, 2015, 5 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/028447, issued Sep. 15, 2015, dated Sep. 24, 2015, 7 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/030692, issued Sep. 15, 2015, dated Sep. 24, 2015, 6 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/064693, issued May 10, 2016, dated May 19, 2016, 14 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/066229, issued May 24, 2016, dated Jun. 6, 2016, 8 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2014/067740, issued May 31, 2016, dated Jun. 9, 2016, 9 Pgs.
International Preliminary Report on Patentability for International Application PCT/US2015/019529, issued Sep. 13, 2016, dated Sep. 22, 2016, 9 Pgs.
International Preliminary Report on Patentability for International Application PCT/US13/62720, Issued Mar. 31, 2015, dated Apr. 9, 2015, 8 Pgs.
International Search Report and Written Opinion for International Application No. PCT/US2015/019529, completed May 5, 2015, dated Jun. 8, 2015, 10 Pgs.
International Search Report and Written Opinion for International Application PCT/US14/21439, completed Jun. 5, 2014, dated Jun. 20, 2014, 10 Pgs.
International Search Report and Written Opinion for International Application PCT/US2010/057661, completed Mar. 9, 2011, 14 pgs.
“File Formats Version 6”, Alias Systems, 2004, 40 pgs.
Bennett et al., “Multispectral Bilateral Video Fusion”, 2007 IEEE Transactions on Image Processing, vol. 16, No. 5, pp. 1185-1194.
Crabb et al., “Real-time foreground segmentation via range and color imaging”, Computer Vision and Pattern Recognition Workshops, 2008. CVPRW'08. IEEE Computer Society Conference on. IEEE, 2008.
Eng, Wei Yong et al., “Gaze correction for 3D tele-immersive communication system”, IVMSP Workshop, 2013 IEEE 11th. IEEE,Jun. 10, 2013.
Hernandez-Lopez et al., “Detecting objects using color and depth segmentation with Kinect sensor”, Procedia Technology, vol. 3, Jan. 1, 2012 (Jan. 1, 2012), pp. 196-204, XP055307680, ISSN: 2212-0173, DOI: 10.1016/j.protcy.2012.03.021.
Huayang et al., “A virtual view synthesis algorithm based on image inpainting”, 2012 Third International Conference on Networking and Distributed Computing. IEEE, 2012.
Rajan et al., “Simultaneous Estimation of Super Resolved Scene and Depth Map from Low Resolution Defocused Observations”, IEEE Computer Society, vol. 25, No. 9; Sep. 2003; pp. 1-16.
Venkataraman et al., “PiCam: An Ultra-Thin High Performance Monolithic Camera Array”, ACM Transactions on Graphics (TOG), ACM, US, vol. 32, No. 6, Nov. 1, 2013 (Nov. 1, 2013), pp. 1-13.
Zheng et al., “Balloon Motion Estimation Using Two Frames”, Proceedings of the Asilomar Conference on Signals, Systems and Computers, IEEE, Comp. Soc. Press, US, vol. 2 of 02, Nov. 4, 1991, pp. 1057-1061.
Extended European Search Report for European Application EP13751714.0, completed Aug. 5, 2015, dated Aug. 18, 2015, 8 Pgs.
Extended European Search Report for European Application No. 14763087.5, Search completed Dec. 7, 2016, dated Dec. 19, 2016, 9 Pgs.
Extended European Search Report for European Application No. 14860103.2, Search completed Feb. 23, 2017, dated Mar. 3, 2017, 7 Pgs.
International Preliminary Report on Patentability for International Application PCT/US10/057661, issued May 22, 2012, dated May 31, 2012, 10 pages.
“Light fields and computational photography”, Stanford Computer Graphics Laboratory, Retrieved from: http://graphics.stanford.edu/projects/lightfield/, Earliest publication online: Feb. 10, 1997, 3 pgs.
Aufderheide et al., “A MEMS-based Smart Sensor System for Estimation of Camera Pose for Computer Vision Applications”, Research and Innovation Conference 2011, Jul. 29, 2011, pp. 1-10.
Bennett et al., “Multispectral Video Fusion”, Computer Graphics (ACM SIGGRAPH Proceedings), Jul. 25, 2006, 1 pg., published Jul. 30, 2006.
Debevec et al., “Recovering High Dynamic Range Radiance Maps from Photographs”, Computer Graphics (ACM SIGGRAPH Proceedings), Aug. 16, 1997, 10 pgs.
Do, Minh N., “Immersive Visual Communication with Depth”, Presented at Microsoft Research, Jun. 15, 2011, Retrieved from: http://minhdo.ece.illinois.edu/talks/ImmersiveComm.pdf, 42 pgs.
Do et al., “Immersive Visual Communication”, IEEE Signal Processing Magazine, vol. 28, Issue 1, Jan. 2011, DOI: 10.1109/MSP.2010.939075, Retrieved from: http://minhdo.ece.illinois.edu/publications/ImmerComm—SPM.pdf, pp. 58-66.
Fang et al., “Volume Morphing Methods for Landmark Based 3D Image Deformation”, SPIE vol. 2710, Proc. 1996 SPIE Intl Symposium on Medical Imaging, Newport Beach, CA, Feb. 10, 1996, pp. 404-415.
Fecker et al., “Depth Map Compression for Unstructured Lumigraph Rendering”, Proc. SPIE 6077, Proceedings Visual Communications and Image Processing 2006, Jan. 18, 2006, pp. 60770B-1-60770B-8.
Georgeiv et al., “Light Field Camera Design for Integral View Photography”, Adobe Systems Incorporated, Adobe Technical Report, 2003, 13 pgs.
Georgiev et al., “Light-Field Capture by Multiplexing in the Frequency Domain”, Adobe Systems Incorporated, Adobe Technical Report, 2003, 13 pgs.
Holoeye, “Spatial Light Modulators”, Photonics AG, Brochure retrieved from http://holoeye.com/wp-content/uploads/Spatial—Light—Modulators.pdf, printed Jun. 15, 2017, 4 pgs.
Konolige, Kurt “Projected Texture Stereo”, 2010 IEEE International Conference on Robotics and Automation, May 3-7, 2010, p. 148-155.
Kubota et al., “Reconstructing Dense Light Field From Array of Multifocus Images for Novel View Synthesis”, IEEE Transactions on Image Processing, vol. 16, No. 1, Jan. 2007, pp. 269-279.
Li et al., “Fusing Images With Different Focuses Using Support Vector Machines”, IEEE Transactions on Neural Networks, vol. 15, No. 6, Nov. 8, 2004, pp. 1555-1561.
Lim, Jongwoo, “Optimized Projection Pattern Supplementing Stereo Systems”, 2009 IEEE International Conference on Robotics and Automation, May 12-17, 2009, pp. 2823-2829.
Martinez et al., “Simple Telemedicine for Developing Regions: Camera Phones and Paper-Based Microfluidic Devices for Real-Time, Off-Site Diagnosis”, Analytical Chemistry (American Chemical Society), vol. 80, No. 10, May 15, 2008, pp. 3699-3707.
Ng et al., “Light Field Photography with a Hand-held Plenoptic Camera”, Stanford Tech Report CTSR 2005-02, Apr. 20, 2005, pp. 1-11.
Nguyen et al., “Error Analysis for Image-Based Rendering with Depth Information”, IEEE Transactions on Image Processing, vol. 18, Issue 4, Apr. 2009, pp. 703-716.
Nguyen et al., “Image-Based Rendering with Depth Information Using the Propagation Algorithm”, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005, vol. 5, Mar. 23-23, 2005, pp. II-589-II-592.
Nishihara, H.K., “PRISM: A Practical Real-Time Imaging Stereo Matcher”, Massachusetts Institute of Technology, A.I. Memo 780, May 1984, 32 pgs.
Park et al., “Multispectral Imaging Using Multiplexed Illumination”, 2007 IEEE 11th International Conference on Computer Vision, Oct. 14-21, 2007, Rio de Janeiro, Brazil, pp. 1-8.
Parkkinen et al., “Characteristic Spectra of Munsell Colors”, Journal of the Optical Society of America A, vol. 6, Issue 2, Feb. 1989, pp. 318-322.
Stober, “Stanford researchers developing 3-D camera with 12,616 lenses”, Stanford Report, Mar. 19, 2008, Retrieved from: http://news.stanford.edu/news/2008/march19/camera-031908.html, 5 pgs.
Taguchi et al., “Rendering-Oriented Decoding for a Distributed Multiview Coding System Using a Coset Code”, Hindawi Publishing Corporation, EURASIP Journal on Image and Video Processing, vol. 2009, Article ID 251081, Online: Apr. 22, 2009, 12 pages.
Vetro et al., “Coding Approaches for End-To-End 3D TV Systems”, Mitsubishi Electric Research Laboratories, Inc., TR2004-137, Dec. 2004, 6 pgs.
Wieringa et al., “Remote Non-invasive Stereoscopic Imaging of Blood Vessels: First In-vivo Results of a New Multispectral Contrast Enhancement Technology”, Annals of Biomedical Engineering, vol. 34, No. 12, Dec. 2006, pp. 1870-1878, Published online Oct. 12, 2006.
Xu, Ruifeng, “Real-Time Realistic Rendering and High Dynamic Range Image Display and Compression”, Dissertation, School of Computer Science in the College of Engineering and Computer Science at the University of Central Florida, Orlando, Florida, Fall Term 2005, 192 pgs.
Yokochi et al., “Extrinsic Camera Parameter Estimation Based-on Feature Tracking and GPS Data”, 2006, Nara Institute of Science and Technology, Graduate School of Information Science, LNCS 3851, pp. 369-378.
Filing Receipt for U.S. Appl. No. 61/527,007, filed Aug. 24, 2011, 25 pgs.
“Exchangeable image file format for digital still cameras: Exif Version 2.2”, Japan Electronics and Information Technology Industries Association, Prepared by Technical Standardization Committee on AV & IT Storage Systems and Equipment, JEITA CP-3451, Apr. 2002, Retrieved from: http://www.exif.org/Exif2-2.PDF, 154 pgs.
Robert et al., “Dense Depth Map Reconstruction: A Minimization and Regularization Approach which Preserves Discontinuities”, European Conference on Computer Vision (ECCV), pp. 439-451, (1996).
Van Der Wal et al., “The Acadia Vision Processor”, Proceedings Fifth IEEE International Workshop on Computer Architectures for Machine Perception, Sep. 13, 2000, Padova, Italy, pp. 31-40.
Related Publications (1)
Number Date Country
20160044257 A1 Feb 2016 US
Provisional Applications (2)
Number Date Country
61775395 Mar 2013 US
61786218 Mar 2013 US