Depth-based image blurring

Information

  • Patent Grant
  • 10552947
  • Patent Number
    10,552,947
  • Date Filed
    Tuesday, November 28, 2017
    6 years ago
  • Date Issued
    Tuesday, February 4, 2020
    4 years ago
Abstract
An image such as a light-field image may be processed to provide depth-based blurring. The image may be received in a data store. At an input device, first and second user input may be received to designate a first focus depth and a second focus depth different from the first focus depth, respectively. A processor may identify one or more foreground portions of the image that have one or more foreground portion depths, each of which is less than the first focus depth. The processor may also identify one or more background portions of the image that have one or more background portion depths, each of which is greater than the second focus depth. The processor may also apply blurring to the one or more foreground portions and the one or more background portions to generate a processed image, which may be displayed on a display device.
Description
TECHNICAL FIELD

The present disclosure relates to systems and methods for processing and displaying image data, and more specifically, to systems and methods for implementing depth-based effects such as blurring of images such as light-field images.


BACKGROUND

In conventional photography, the camera must typically be focused at the time the photograph is taken. The resulting image may have only color data for each pixel; accordingly, any object that was not in focus when the photograph was taken cannot be brought into sharper focus because the necessary data does not reside in the image.


By contrast, light-field images typically encode additional data for each pixel related to the trajectory of light rays incident to that pixel when the light-field image was taken. This data can be used to manipulate the light-field image through the use of a wide variety of rendering techniques that are not possible to perform with a conventional photograph. In some implementations, a light-field image may be refocused and/or altered to simulate a change in the center of perspective (CoP) of the camera that received the image. Further, a light-field image may be used to generate an enhanced depth-of-field (EDOF) image in which all parts of the image are in focus. A depth map can typically be obtained from a light-field image, indicating the depth at which objects in the light-field image were disposed, relative to the light-field camera, at the time the light-field image was captured.


Existing techniques for processing conventional images are limited in many respects. Specifically, editing conventional images to provide effects, such as changing colorization, contrast, or objects in the image, can be challenging. Typically, the user must employ careful selection of object boundaries to control how the effects are applied. Accordingly, application of effects in conventional images can be a time-consuming and labor-intensive effort. Existing processing and effect application techniques for light-field images often do not make full use of the information in the light-field image, or utilize a user interface that makes it difficult for the user to locate and apply the desired effect.


SUMMARY

According to various embodiments, the system and method described herein facilitate customization of image properties such as depth of field. The customized depth of field may be used to control various image processes, such as blurring and/or bokeh effects in foreground and/or background portions of the image. When applied to an image accompanied by sufficient depth information, the system and method may enable the user to easily designate depth levels within an image, such as background, subject, and foreground levels, based on depth and without the need to manually select the corresponding image portion(s).


An image such as a light-field image may be captured with a light-field image capture device with a microlens array. The image may be received in a data store along with a depth map that indicates depths at which objects in the image are disposed, relative to the camera, at the time of image capture. At an input device, first and second user input may be received to designate a first focus depth and a second focus depth different from the first focus depth, respectively. The first focus depth may indicate the far limit (i.e., maximum depth) of an image foreground, and the second focus depth may indicate the near limit (i.e., the minimum depth) of an image background.


A processor may use the first focus depth to identify the image foreground. The image foreground may have one or more foreground portions that have one or more foreground portion depths, each of which is less than the first focus depth. Similarly, the processor may also use the second focus depth to identify the image background. The image background may have one or more background portions that have one or more background portion depths, each of which is greater than the second focus depth.


Once the image foreground and the image background have been identified, the processor may apply blurring and/or other effects to the one or more foreground portions and/or the one or more background portions to generate a processed image. The processed image may have, for example, an image subject including one or more subject portions that have one or more subject portion depths, each of which is between the first focus depth and the second focus depth. The image subject may optionally be in focus, and blurring may be applied to the image foreground and the image background in proportion to the difference in depth between each foreground portion and each background portion from the subject portion. Thus, a foreground portion with a depth that is much smaller, relative to the image subject, may have more blurring applied to it than a foreground portion with a depth that is nearly as large as the first focus depth. Similarly, a background portion with a depth that is much greater, relative to the image subject, may have more blurring applied to it than a background portion with a depth that is only just larger than the second focus depth.


The processed image may be displayed on a display device. The user may make further adjustments, such as adjusting the first focus depth and/or the second focus depth again, until the desired effect is obtained. Various user interface elements, controls, and the like may be provided to the user to facilitate determination of the first and second focus depths and/or control application of depth-based effects such as blurring. In addition to or in the alternative to application of blurring, the designated first and second focus depths may be used to control application of bokeh effects such as the application of blur effects, which may be circular, noncircular, and/or variable with depth. Further, the blurring and bokeh effects are merely exemplary; the system and method disclosed herein may be used to apply a wide variety of other effects besides blurring and bokeh effects. Such effects may include, but are not limited to, modification of exposure, contrast, saturation, and/or colorization of the image, replacement of a portion of an image with another image or portion thereof, and/or the like. Hence, it will be understood that reference to application of “blurring” in this disclosure is also disclosure of any other depth-based effect.


Application of blurring, bokeh effects, and/or other effects may be varied linearly with depth and/or nonlinearly with depth, as desired. Additionally or alternatively, application of such effects may be varied linearly and/or nonlinearly based on the X coordinate and/or the Y coordinate of the pixel to be blurred. Thus, blurring maybe applied with greater intensity toward the top, bottom, center, and/or edges of an image.





BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings illustrate several embodiments. Together with the description, they serve to explain the principles of the embodiments. One skilled in the art will recognize that the particular embodiments illustrated in the drawings are merely exemplary, and are not intended to limit scope.



FIG. 1 depicts a portion of a light-field image.



FIG. 2 depicts an example of an architecture for implementing the methods of the present disclosure in a light-field capture device, according to one embodiment.



FIG. 3 depicts an example of an architecture for implementing the methods of the present disclosure in a post-processing system communicatively coupled to a light-field capture device, according to one embodiment.



FIG. 4 depicts an example of an architecture for a light-field camera for implementing the methods of the present disclosure according to one embodiment.



FIGS. 5A and 5B are graphs indicating traditional and range-limited methods, respectively, of processing an image based on depth of field.



FIG. 6 is a flow diagram depicting a method of carrying out depth-based blurring of an image, according to one embodiment.



FIG. 7 is a screenshot diagram depicting an exemplary user interface for initiation of depth-based image processing, showing an exemplary image, according to one embodiment.



FIG. 8 is a screenshot diagram depicting the user interface of FIG. 7, showing a depth map, according to one embodiment.



FIG. 9 is a screenshot diagram depicting the user interface FIG. 7 during selection of a new first focus depth, according to one embodiment.



FIG. 10 is a screenshot diagram depicting the user interface of FIG. 7 after blurring of foreground portions of the image in response to selection of the new first focus depth, according to one embodiment.



FIG. 11 is a screenshot diagram depicting the user interface of FIG. 7 during selection of a new second focus depth, according to one embodiment.



FIG. 12 is a screenshot diagram depicting the image of FIG. 7 after blurring of background portions of the image in response to selection of the new second focus depth, according to one embodiment.



FIGS. 13A and 13B are screenshot diagrams depicting the focus spread toolbox of the user interface of FIG. 7, in a positive-only spread mode and a negative spread mode, respectively, according to one embodiment.



FIGS. 14A and 14B are screenshot diagrams depicting the focus spread toolbox of the user interface of FIG. 7, illustrating movement of the entire focus slider, according to one embodiment.



FIGS. 15A and 15B are screenshot diagrams depicting the focus spread toolbox of the user interface of FIG. 7, before and after clicking on the focus slider, according to one embodiment.



FIGS. 16A and 16B are screenshot diagrams depicting the focus spread toolbox of the user interface of FIG. 7, before and after clicking and dragging the focus slider to move both the first focus distance and the second focus distance off of the focus slider, respectively, according to one embodiment.



FIG. 17 is a screenshot diagram depicting an exemplary user interface for initiation of depth-based image processing, showing an exemplary image, according to another embodiment.



FIG. 18 is a screenshot diagram depicting the exemplary user interface of FIG. 17, with the focus spread overlay toggled to “On,” according to one embodiment.



FIG. 19 is a screenshot diagram depicting the exemplary user interface of FIG. 17, after the user has moved the first focus marker and the second focus marker apart, according to one embodiment.



FIG. 20 is a screenshot diagram depicting the exemplary user interface of FIG. 17, after the user has designated a location in the image to refocus the image to that location.



FIG. 21 is a screenshot diagram depicting the exemplary user interface of FIG. 17 after user designation of a location on the image as in FIG. 20, and after the focus spread overlay has been enabled.



FIG. 22 is a screenshot diagram depicting the exemplary user interface of FIG. 17 after the user has designated a different location on the image to refocus the image to that location.



FIG. 23 is a screenshot diagram depicting the exemplary user interface of FIG. 17 after user designation of a different location on the image as in FIG. 22, and after the focus spread overlay has been enabled.



FIG. 24 is a screenshot diagram depicting the exemplary user interface of FIG. 17 after modification of the tilt controls in the tilt toolbox of the editing pane.



FIG. 25 is a screenshot diagram depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider and the rotation slider in FIG. 24, and after the focus spread overlay has been enabled.



FIG. 26 is a screenshot diagram depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider and the rotation slider in FIG. 24, and after the user has designated another different location on the image to refocus the image to that location.



FIG. 27 is a screenshot diagram depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider and the rotation slider in FIG. 24 and designation of a new in-focus region in FIG. 26, and after the focus spread overlay has been enabled.



FIG. 28 is a screenshot diagram depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider and the rotation slider in FIG. 24, and after the user has designated another different location on the image to refocus the image to that location.



FIG. 29 is a screenshot diagram depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider and the rotation slider in FIG. 24 and designation of a new in-focus region in FIG. 28, and after the focus spread overlay has been enabled.



FIGS. 30A, 30B, 30C, and 30D are schematic block diagrams of various blur shapes that may be used to apply bokeh effects, according to exemplary embodiments.



FIGS. 31A and 31B are graphs illustrating linear and nonlinear application of blur effects, respectively, according to exemplary embodiments.





DEFINITIONS

For purposes of the description provided herein, the following definitions are used:

    • Background portion: a portion of an image in which one or more objects are further from the camera, relative to one or more other portions of the image.
    • Bokeh effects: effects that can be applied to one or more out-of-focus areas of an image.
    • Depth: a representation of distance between an object and/or corresponding image sample and a microlens array of a camera.
    • Depth map: a two-dimensional map corresponding to a light-field image, indicating a depth for each of multiple pixel samples within the light-field image.
    • Disk: a region in a light-field image that is illuminated by light passing through a single microlens; may be circular or any other suitable shape.
    • Extended depth of field (EDOF) image: an image that has been processed to have objects in focus along a greater depth range.
    • Gradual transition: a transition in application of an effect to an image that provides for partial application of the effect to at least a portion of the image, with no discontinuity between affected, partially-affected, and unaffected areas, as applicable.
    • Focus depth: a depth within an image on which a depth-based process is to be based.
    • Foreground portion: a portion of an image in which one or more objects are closer to the camera, relative to one or more other portions of the image.
    • Function: a mathematical relationship that provides one or more outputs for each set of one or more inputs.
    • Image: a two-dimensional array of pixel values, or pixels, each specifying a color.
    • Light-field data: data indicative of the intensity and origin of light received within a system such as a light-field camera.
    • Light-field image: an image that contains a representation of light-field data captured at the sensor.
    • Linear function: a function represented by a straight line.
    • Mask: a description of the degree to which an effect is to be applied to an image; may be (but need not be) a pictorial grayscale overlay of the image.
    • Microlens: a small lens, typically one in an array of similar microlenses.
    • Nonlinear function: a function that is not represented by a straight line.
    • Processed light-field image: the resulting image after one or more processing steps are applied to a light-field image.
    • Subject portion: a portion of an image that is to be featured in the image; typically (but not necessarily) to be in focus.
    • Tilt: the rotation of a focus plane such that the focus plane is not at a uniform depth, relative to the camera.


In addition, for ease of nomenclature, the term “camera” is used herein to refer to an image capture device or other data acquisition device. Such a data acquisition device can be any device or system for acquiring, recording, measuring, estimating, determining and/or computing data representative of a scene, including but not limited to two-dimensional image data, three-dimensional image data, and/or light-field data. Such a data acquisition device may include optics, sensors, and image processing electronics for acquiring data representative of a scene, using techniques that are well known in the art. One skilled in the art will recognize that many types of data acquisition devices can be used in connection with the present disclosure, and that the disclosure is not limited to cameras. Thus, the use of the term “camera” herein is intended to be illustrative and exemplary, but should not be considered to limit the scope of the disclosure. Specifically, any use of such term herein should be considered to refer to any suitable device for acquiring image data.


In the following description, several techniques and methods for processing light-field images are described. One skilled in the art will recognize that these various techniques and methods can be performed singly and/or in any suitable combination with one another.


Architecture


In at least one embodiment, the system and method described herein can be implemented in connection with light-field images captured by light-field capture devices including but not limited to those described in Ng et al., Light-field photography with a hand-held plenoptic capture device, Technical Report CSTR 2005-02, Stanford Computer Science. Referring now to FIG. 2, there is shown a block diagram depicting an architecture for implementing the method of the present disclosure in a light-field capture device such as a camera 200. Referring now also to FIG. 3, there is shown a block diagram depicting an architecture for implementing the method of the present disclosure in a post-processing system 300 communicatively coupled to a light-field capture device such as a camera 200, according to one embodiment. One skilled in the art will recognize that the particular configurations shown in FIGS. 2 and 3 are merely exemplary, and that other architectures are possible for camera 200. One skilled in the art will further recognize that several of the components shown in the configurations of FIGS. 2 and 3 are optional, and may be omitted or reconfigured.


In at least one embodiment, camera 200 may be a light-field camera that includes light-field image data acquisition device 209 having optics 201, image sensor 203 (including a plurality of individual sensors for capturing pixels), and microlens array 202. Optics 201 may include, for example, aperture 212 for allowing a selectable amount of light into camera 200, and main lens 213 for focusing light toward microlens array 202. In at least one embodiment, microlens array 202 may be disposed and/or incorporated in the optical path of camera 200 (between main lens 213 and sensor 203) so as to facilitate acquisition, capture, sampling of, recording, and/or obtaining light-field image data via sensor 203. Referring now also to FIG. 4, there is shown an example of an architecture for a light-field camera 200 for implementing the method of the present disclosure according to one embodiment. The Figure is not shown to scale. FIG. 4 shows, in conceptual form, the relationship between aperture 212, main lens 213, microlens array 202, and sensor 203, as such components interact to capture light-field data for subject 401.


In at least one embodiment, light-field camera 200 may also include a user interface 205 for allowing a user to provide input for controlling the operation of camera 200 for capturing, acquiring, storing, and/or processing image data.


Similarly, in at least one embodiment, post-processing system 300 may include a user interface 305 that allows the user to provide input to control and/or activate depth-based image processing, as set forth in this disclosure. The user interface 305 may facilitate the receipt of user input from the user to establish one or more parameters of the image processing process.


In at least one embodiment, light-field camera 200 may also include control circuitry 210 for facilitating acquisition, sampling, recording, and/or obtaining light-field image data. For example, control circuitry 210 may manage and/or control (automatically or in response to user input) the acquisition timing, rate of acquisition, sampling, capturing, recording, and/or obtaining of light-field image data.


In at least one embodiment, camera 200 may include memory 211 for storing image data, such as output by image sensor 203. Such memory 211 can include external and/or internal memory. In at least one embodiment, memory 211 can be provided at a separate device and/or location from camera 200, such as the post-processing system 300.


For example, camera 200 and/or the post-processing system 300 may store raw light-field image data, as output by sensor 203, and/or a representation thereof, such as a compressed image data file. In addition, as described in related U.S. Utility application Ser. No. 12/703,367 for “Light-field Camera Image, File and Configuration Data, and Method of Using, Storing and Communicating Same,”, filed Feb. 10, 2010, memory 211 can also store data representing the characteristics, parameters, and/or configurations (collectively “configuration data”) of device 209.


In at least one embodiment, captured image data is provided to post-processing circuitry 204. Such circuitry 204 may be disposed in or integrated into light-field image data acquisition device 209, as shown in FIG. 2, or it may be in a separate component external to light-field image data acquisition device 209, such as the post-processing system 300 of FIG. 3. Such separate component may be local or remote with respect to light-field image data acquisition device 209. Any suitable wired or wireless protocol can be used for transmitting image data 221 to circuitry 204; for example camera 200 can transmit image data 221 and/or other data via the Internet, a cellular data network, a WiFi network, a Bluetooth communication protocol, and/or any other suitable means.


The post-processing system 300 may include any of a wide variety of computing devices, including but not limited to computers, smartphones, tablets, cameras, and/or any other device that processes digital information. The post-processing system 300 may include additional features such as a user input 215 and/or a display screen 216. If desired, light-field image data may be displayed for the user on the display screen 216.


Overview


Light-field images often include a plurality of projections (which may be circular or of other shapes) of aperture 212 of camera 200, each projection taken from a different vantage point on the camera's focal plane. The light-field image may be captured on sensor 203. The interposition of microlens array 202 between main lens 213 and sensor 203 causes images of aperture 212 to be formed on sensor 203, each microlens in microlens array 202 projecting a small image of main-lens aperture 212 onto sensor 203. These aperture-shaped projections are referred to herein as disks, although they need not be circular in shape. The term “disk” is not intended to be limited to a circular region, but can refer to a region of any shape.


Light-field images include four dimensions of information describing light rays impinging on the focal plane of camera 200 (or other capture device). Two spatial dimensions (herein referred to as x and y) are represented by the disks themselves. For example, the spatial resolution of a light-field image with 120,000 disks, arranged in a Cartesian pattern 400 wide and 300 high, is 400×300. Two angular dimensions (herein referred to as u and v) are represented as the pixels within an individual disk. For example, the angular resolution of a light-field image with 100 pixels within each disk, arranged as a 10×10 Cartesian pattern, is 10×10. This light-field image has a 4-D (x,y,u,v) resolution of (400,300,10,10). Referring now to FIG. 1, there is shown an example of a 2-disk by 2-disk portion of such a light-field image, including depictions of disks 102 and individual pixels 101; for illustrative purposes, each disk 102 is ten pixels 101 across.


In at least one embodiment, the 4-D light-field representation may be reduced to a 2-D image through a process of projection and reconstruction. As described in more detail in related U.S. Utility application Ser. No. 13/774,971 for “Compensating for Variation in Microlens Position During Light-Field Image Processing,” filed Feb. 22, 2013, the disclosure of which is incorporated herein by reference in its entirety, a virtual surface of projection may be introduced, and the intersections of representative rays with the virtual surface can be computed. The color of each representative ray may be taken to be equal to the color of its corresponding pixel.


Any number of image processing techniques can be used to reduce color artifacts, reduce projection artifacts, increase dynamic range, and/or otherwise improve image quality. In particular, enhanced depth-of-field (EDOF) images may be created, in which all parts of the image are in focus. However, in many instances the user may wish to fine tune the depth of field of the image to keep one or more portions of the image in focus. For example, the user may wish to designate an image subject that is to be in focus, while an image background and/or an image foreground are blurred. Such image processing may be facilitated by the system and method provided herein.


Depth-Based Image Processing


The system and method of the present disclosure may facilitate user control over which portions of the image are in focus, and which are blurred. Further, the system and method of the present disclosure may facilitate user control over the application of other effects besides blurring, which include but are not limited to modification of exposure, contrast, saturation, and/or colorization of the image, replacement of a portion of an image with another image or portion thereof, and/or the like. Further, the user may have greater control over the manner in which blurring is applied. This will be conceptually illustrated in connection with FIGS. 5A and 5B.



FIGS. 5A and 5B are graphs 500, 550 indicating traditional and range-limited methods, respectively, of processing an image based on depth of field. Each of the graphs 500, 550 may have a horizontal axis 510 that represents the distance of objects in the image from the camera, and a vertical axis 520 that represents the blurriness of those objects.


The graph 500 of FIG. 5A illustrates traditional processing, which is the default condition for conventional imaging without the benefit of light-field image capture technology. The image may have a focus point 530 at which objects are in focus. At distances from the camera shorter than that of the focus point 530, blurriness may increase with decreased distance. Similarly, at distances from the camera greater than that of the focus point 530, blurriness may increase with increased distance.


The graph 550 of FIG. 5B illustrates processing that may be carried out according to the system and method presented herein. In place of the focus point 530, the image of FIG. 5B may have a focus range 560, within which all objects are in focus. The focus range 560 may extend from a first focus depth 570 to a second focus depth 580. At distances from the camera shorter than that of the first focus depth 570, blurriness may increase with decreased distance. Similarly, at distances from the camera greater than that of the second focus depth 580, blurriness may increase with increased distance.


The system and method presented herein may advantageously provide the user with the ability to determine which portion of the image is in focus by designating the first focus depth 570 and the second focus depth 580. Further, if desired, the user may designate the manner in which blur is applied to the foreground and/or background portions of the image. One exemplary method will be shown and described in connection with FIG. 6, and then illustrated in connection with the screenshot diagrams of FIG. 7 through FIG. 12.



FIG. 6 is a flow diagram depicting a method of carrying out depth-based blurring of an image, according to one embodiment. The method may be performed with any image for which depth information is available. Thus, the method of FIG. 6 may be used in connection with stereoscopic, multi-scopic, and light-field images, or even with conventional images for which depth information has been obtained (for example, through depth measurements made with other instruments at the time of image capture, through the manual entry of depth information by the user, or the like). The following description is based on the example of processing a light-field image, but those of skill in the art will recognize how the method of FIG. 6 may be adapted for use with other image types.


The method may be performed, for example, with circuitry such as the post-processing circuitry 204 of the camera 200 of FIG. 2 or the post-processing circuitry 204 of the post-processing system 300 of FIG. 3, which is independent of the camera 200. In some embodiments, a computing device may carry out the method; such a computing device may include one or more of desktop computers, laptop computers, smartphones, tablets, cameras, and/or other devices that process digital information.


The method may start 600 with a step 610 in which the image (for example, a light-field image) is captured, for example, by the sensor 203 of the camera 200. In a step 620, the image may be received in a computing device, which may be the camera 200 as in FIG. 2. Alternatively, the computing device may be separate from the camera 200 as in the post-processing system 300 of FIG. 3, and may be any type of computing device, including but not limited to desktop computers, laptop computers, smartphones, tablets, and the like.


In a step 630, user input may be received (for example, in the camera 200 and/or the post-processing system 300) to designate the first focus depth 570. This designation may be made in a variety of ways, including but not limited to text entry, speech, selection from a menu, clicking or tapping on an indicator such as a slider, selecting a portion of the image, and/or the like.


In a step 640, user input may be received (for example, in the camera 200 and/or the post-processing system 300) to designate the second focus depth 580. This designation may also be made in a variety of ways, including but not limited to text entry, speech, selection from a menu, clicking or tapping on an indicator such as a slider, selecting a portion of the image, and/or the like.


In a step 650, one or more foreground portions of the image may be identified. This may be done, for example, automatically by the camera 200 and/or the post-processing system. This may be accomplished by referencing the depth information corresponding to the image. Such depth information may take the form of a depth map in which intensity levels, colors, and/or other characteristics are used to indicate the depth at which objects in corresponding portions of the image were positioned, relative to the camera, at the time of image capture. Thus, for example, such a depth map may be used to automatically identify all portions of the image having a depth less than that of the first focus depth received in the step 630.


In a step 660, one or more background portions of the image may be identified. This may be done, for example, automatically by the camera 200 and/or the post-processing system. As in the step 650, this may be accomplished by referencing the depth map or other depth information corresponding to the image. For example, such a depth map may be used to automatically identify all portions of the image having a depth greater than that of the second focus depth received in the step 640.


In a step 670, blurring may be applied to the one or more foreground portions identified in the step 650 and/or to the one or more background portions identified in the step 660. Blurring may be applied through the application of one or more known blurring techniques, which may include mixing color and/or intensity values of a pixel to be blurred with those of surrounding pixels.


More specifically, ignoring the sampling issues caused by the fact that there are a finite number of pixel samples, a fully generalized blur function may be implemented. For example, the 2D bokeh of a point light source may be expressed as an arbitrary function of the three-dimensional coordinates of the point. This may make blur a five-dimensional function. During light-field projection, the five-dimensional function may be implemented as an individual three-dimensional function for each microlens of the two-dimensional array of microlenses (the microlens array 202 of FIG. 2). The individual three-dimensional function may specify the contribution of each sample behind the microlens array 202 as a function of the object distance of the ray source of each sample (one-dimensional variation).


The five-dimensional function may be implemented as an individual three-dimensional function for each pixel of the processed image. Each three-dimensional function may specify the contribution of each pixel in the EDOF source image, as a function of the depth of that pixel. A wide variety of blur-related viewing features, including but not limited to focus distance, depth of field, tilt, focus spread, and additional blur may be implemented as simplified ways to specify the generalized five-dimensional blur function. The five dimensions may be as follows: Point X, Point Y, Point Z, Bokeh X, and Bokeh Y. The blur-related viewing features listed above may be implemented as follows:

    • Focus distance may shift the entire function along its Point Z dimension;
    • Depth of field may scale the entire function along its Point Z dimension, centered around the focus distance;
    • Tilt may shift the entire function along its Point Z dimension, by an amount that is, itself, a linear function of (Point X/Point Z) and/or (Point Y/Point Z);
    • Focus spread may push the function away from the focus distance in both directions along the Point Z dimension; and
    • Additional Blur may scale Bokeh X and bokeh Y by an additional value (for example, (1.0+the additional blur).


As implemented in light-field projection, generalized blur may also be used to implement higher-level parallax effects such as center-of-perspective and stereo projection. These may simply weight the contributions of the samples behind each microlens in a way that is not radially symmetrical.


Once the desired blurring has been applied, the processed image may be displayed, for example, on the display screen 216 of the post-processing system 300, in a step 680. Then, in a query 690, a determination may be made as to whether the user wishes to modify the focus range, for example, by receiving input from the user via an input device such as the user input 215 of the post-processing system 300 or an input device of the camera 200. If so, the method may return to the step 630 and/or the step 640 so that the user can modify the first focus depth 570 and/or the second focus depth 580. The method may proceed through the step 650, the step 660, the step 670, the step 680, and the query 690 until the user is satisfied with the focus range of the image. When the user is satisfied with the focus range of the image, the query 690 may be answered in the negative. The method may then end 698.


The method of FIG. 6 is only one of many possible methods that may be used to apply depth-based image processing. According to various alternatives, various steps of FIG. 6 may be carried out in a different order, omitted, and/or replaced by other steps. For example, other image processing steps such as color space conversion, blurring, Automatic White Balance (AWB) algorithms and/or any other image processing steps set forth above may be incorporated into the method of FIG. 6, at any stage of the method, and may be carried out with respect to the image prior to, during, and/or after application of effects.


In other examples, the first focus depth 570 and/or the second focus depth 580 may be used to apply different depth-based image processing steps. For example, any known bokeh effect may be applied, including the use of one or more blur shapes in the foreground and/or background. Such shapes need not be circular, and may vary with depth. In yet other examples, linear and/or nonlinear functions may be used to apply blurring and/or other depth-based effects. Examples of such modifications will be shown and described after the description of an exemplary user interface in FIGS. 7 through 29.


EXAMPLES


FIG. 7 is a screenshot diagram 700 depicting initiation of processing of an image 710, according to one embodiment. The screenshot diagram 700 illustrates the use of a user interface that facilitates application of depth-based processing to the image 710. The image 710 may be a light-field image, or may be obtained via initial processing of a light-field image. In an alternative embodiment, image 710 may be any other type of image, and need not be a light-field image, as described above.


The image 710 may have a subject portion 712 that the user may wish to keep focused (the boy's face), a foreground portion 714 (the boy's hand and the plane he is holding) closer to the camera than the subject portion 712, and a background portion 716 (the sky, trees, and ground) further from the camera than the subject portion 712. Notably, in FIG. 7, the focus range is broad enough to encompass substantially the entire image; accordingly, the foreground portion 714 and the background portion 716 are not labeled. These portions of the image 710 will be labeled in subsequent figures in which the focus spread of the image 710 is narrowed to provide blurring of the foreground portion 714 and the background portion 716.


As shown, the user interface may display the image 710, and may also display an editing pane 720 in which the user can make various modifications to the image 710. The editing pane 720 may include a focus spread toolbox 730 in which the user can customize the manner in which the image 710 is focused. The editing pane 720 may also include various other toolboxes that can be used to modify other aspects of the image 710.


The focus spread toolbox 730 may, for example, have a focus indicator 740 that indicates the depth at which the image 710 is focused. This may be the first focus depth 570, the second focus depth 580, the average of the first focus depth 570 and the second focus depth 580, and/or any other value indicative of focus depth. The focus spread toolbox 730 may also have a spread indicator 742 that indicates the size of the depth of field, or the size of the focus spread of the image 710. Further, the focus spread toolbox 730 may have a mode indicator 744 that indicates a mode in which the user is currently using the focus spread toolbox 730.


Further, the focus spread toolbox 730 may have a focus slider 750 that can be used to adjust the first focus depth 570 and/or the second focus depth 580. The focus slider 750 may have various elements that facilitate this adjustment, such as a first focus marker 752 and a second focus marker 754. The first focus marker 752 may be positioned at the first focus depth 570, and the second focus marker 754 may be positioned at the second focus depth 580.


The first focus marker 752 and the second focus marker 754 may divide the focus slider 750 into a subject portion 762, a foreground portion 764, and a background portion 766. The left-hand side of the focus slider 750 may represent smaller depth (i.e., objects in the image 710 that are closer to the camera), with depth gradually increasing toward the right-hand side of the focus slider 750. The subject portion 762, the foreground portion 764, and the background portion 766 of the focus slider 750 may correspond to the subject portion 712, the foreground portion 714, and the background portion 716 of the image 710, respectively.


The first focus marker 752 and the second focus marker 754 may be used to set the first focus depth 570 and the second focus depth 580, respectively. If desired, the user may click or tap and drag the first focus marker 752 to the left or right to decrease or increase, respectively, the first focus depth 570. Similarly, the user may click or tap and drag the second focus marker 754 to the left or right to decrease or increase, respectively, the second focus depth 580. Moving the first focus marker 752 to the left may cause portions of the foreground portion 714 of the image 710 to be included in the subject portion 712 rather than the foreground portion 714. Similarly, moving the second focus marker 754 to the right may cause portions of the background portion 716 of the image 710 to be included in the subject portion 712 rather than the background portion 716. The focus slider 750 may be manipulated in various other ways, as will be set forth in connection with FIGS. 13A through 16B.


If desired, no blurring may be applied to the subject portion 712, designated by the subject portion 762 of the focus slider 750. Blurring may be applied to the foreground portion 714 and the background portion 716, with increasing blur applied to portions of the image 710 that are further displaced from the depth of the subject portion 712. This may cause the largest blur to be applied to objects in the image 710 that are closest to and/or furthest from the camera.


In addition to the focus slider 750 and related elements, the focus spread toolbox 730 may have a foreground dropper 774 and a background dropper 776. The foreground dropper 774 and the background dropper 776 may provide an alternative mechanism to manipulation of the first focus marker 752 and the second focus marker 754 to set the first focus depth 570 and the second focus depth 580, respectively. For example, the user may click on the foreground dropper 774 and then click on a portion of the image 710 that is at the desired depth for the first focus depth 570. The first focus depth 570 may then be set to the depth of the portion of the image 710 that was selected with the foreground dropper 774. Similarly, the user may click on the background dropper 776 and then click on a portion of the image 710 that is at the desired depth for the second focus depth 580. The second focus depth 580 may then be set to the depth of the portion of the image 710 that was selected with the background dropper 776.


If neither the foreground dropper 774 nor the background dropper 776 has been selected, the user may click, tap, or otherwise designate a portion of the image 710 at which the image 710 is to be focused. The result may be movement of the subject portion 762 of the focus slider 750 to center on a depth corresponding to that of the selected location of the image 710. This method of refocusing an image will be shown and described in greater detail subsequently, in connection with FIGS. 17 through 29.


In addition to the focus spread toolbox 730, the editing pane 720 may have other toolboxes such as a depth map toolbox 780 and a tilt toolbox 790. The depth map toolbox 780 may have a depth map button 792 that may be clicked or otherwise selected to initiate display of the depth map corresponding to the image 710. The depth map toolbox 780 may also have an image button 794 that may be clicked or otherwise selected to return to display of the image 710. Display of the depth map will be shown and described in connection with FIG. 8.



FIG. 8 is a screenshot diagram 800 depicting the user interface of FIG. 7, showing a depth map 810, according to one embodiment. This view may be shown after the user has selected the depth map button 792 as described above. The depth map 810 may correspond to the image 710, and may be in grayscale with pixel intensities that indicate the depth of each portion of the image 710. For example, lower intensities (darker pixels) may correspond to lower depths (as in the foreground portion 714) and higher intensities (brighter pixels) may correspond to higher depths (as in the background portion 716).


The depth map 810 may help the user to more easily visualize the depth of each portion of the image 710. Thus, viewing the depth map 810 may help the user to understand the likely effects of manipulating the focus slider 750.


As indicated previously, the user may select the image button 794 to once again display the image 710 as in FIG. 7. In FIG. 7, the subject portion 712, the foreground portion 714, and the background portion 716 are generally in focus. The user may move the first focus marker 752 to control where the depth boundary is between the subject portion 712 and the foreground portion 714. For example, if the user clicks and drags the first focus marker 752 to the right, the result will be to cause some regions of the subject portion 712 to enter the foreground portion 714, where they will be subject to blurring. The foreground portion 714 may be colored during motion of the first focus marker 752 to help the user to visualize which portions of the image 710 will be blurred if the first focus marker 752 remains at its current position. The resulting view will be shown in FIG. 9.



FIG. 9 is a screenshot diagram 900 depicting the user interface FIG. 7 during selection of a new first focus depth 570, according to one embodiment. As shown, the foreground portion 714 of the image 710 is colored with a blue pattern so that the user can easily visualize the portion of the image 710 that will be blurred with the first focus marker 752 at its current position. The blue pattern may expand, shrink, and/or move to or from other areas of the image 710 in real-time as the first focus marker 752 moves to further enhance visualization. Thus, the user can easily determine which portion(s) of the image 710 are to be blurred as foreground portions of the image 710. If the user releases the first focus marker 752, the portion of the image 710 with the blue pattern will be blurred. The resulting view is shown in FIG. 10.



FIG. 10 is a screenshot diagram 1000 depicting the user interface of FIG. 7 after blurring of the foreground portion 714 of the image 710 in response to selection of the new first focus depth 570, according to one embodiment. As shown, the foreground portion 714 of the image 710 now includes the plane and the boy's hand, which are therefore now blurred, reflecting the fact that the first focus marker 752 has been moved to the right to expand the foreground portion 714. This may reduce the size of the subject portion 712, but may also draw attention to particular aspects of the subject portion 712, such as the boy's face.


The user may follow a similar procedure to expand the background portion 716 of the image 710 to cause blurring of objects at a greater depth from the camera. The user may move the second focus marker 754 to the left to reduce the second focus depth 580, thereby causing objects with a depth greater than the second focus depth 580 (in the depth map 810) to be blurred. As with adjustment of the foreground portion 714, adjustment of the background portion 716 may be visualized through the use of a color pattern to show the background portion 716. This will be shown in FIG. 11.



FIG. 11 is a screenshot diagram 1100 depicting the user interface of FIG. 7 during selection of a new second focus depth 580, according to one embodiment. As shown, an orange pattern illustrates the portions of the image 710 that will be included in the background portion 716, if the second focus marker 754 remains at its current position on the focus slider 750. These portions of the image 710 may be blurred, as will be shown in FIG. 12.



FIG. 12 is a screenshot diagram 1200 depicting the image of FIG. 7 after blurring of the background portion 716 of the image 710 in response to selection of the new second focus depth 580, according to one embodiment. As shown, some blurring has been applied to the trees and the sky behind the boy. This blurring may be applied to the portions of the image 710 that were shown with the orange pattern in FIG. 11. This blurring may serve to further draw attention to the boy's face.


In the alternative to the use of the first focus marker 752 and the second focus marker 754 to obtain the blurring of FIG. 12, the foreground dropper 774 and/or the background dropper 776 may be used. For example, the user may use the foreground dropper 774 to select a location on the boy's arm, indicating that the boy's hand and the plane are to be included in the foreground portion 714. Similarly, the user may use the background dropper 776 to select a location on the ground to indicate that the ground, trees, and sky behind that selected should be included in the background portion 716.


The focus spread toolbox 730 may be manipulated in various other ways to further facilitate user designation of how the image 710 is to be focused and/or blurred. Some of these will be shown and described in connection with FIGS. 13A through 16B.



FIGS. 13A and 13B are screenshot diagrams 1300 and 1350 depicting the focus spread toolbox 730 of the user interface of FIG. 7, in a positive-only spread mode and a negative spread mode, respectively, according to one embodiment. As indicated previously, the mode indicator 744 may indicate the mode in which the user is currently interacting with the focus spread toolbox 730.


Specifically, the mode indicator 744 of FIG. 13A may indicate that the user is in the positive-only spread mode. In such a mode, the first focus marker 752 and the second focus marker 754 may not be dragged past each other. Thus, the user may be able to reduce the focus spread to zero, but a negative focus spread would not be possible. If the user wishes to enable the use of a negative focus spread, he or she may click, tap, or otherwise select the mode indicator 744 to change to a negative spread mode. The resulting view is shown in FIG. 13B.


In FIG. 13B, the mode indicator 744 has changed to indicate that the user is using the toolbox 730 in the negative spread mode. In this mode, the user may select and move either of the first focus marker 752 and the second focus marker 754 past the other. In FIG. 13B, the user has clicked and dragged the first focus marker 752 to the right in the direction of the arrow 1360, past the second focus marker 754. The result is the presence of a negative spread portion 1370 (colored red instead of white to indicate that it is a negative spread portion) in place of the subject portion 762. This substitution may be done because the subject portion 762 may not be present—no part of the image 710 may be in focus. Rather, the entire image 710 may be blurred. The blurring may be least within the negative spread portion 1370, and may increase with increasing depth differential relative to the negative spread portion 1370.


If the user again selects the mode indicator 744, the focus spread toolbox 730 may return to the positive-only spread mode. Further, the first focus marker 752 and the second focus marker 754 may move together to eliminate the negative spread portion 1370. The user may then again be unable to move the first focus marker 752 to the right of the second focus marker 754, or move the second focus marker 754 to the left of the first focus marker 752.



FIGS. 14A and 14B are screenshot diagrams 1400, 1450 depicting the focus spread toolbox 730 of the user interface of FIG. 7, illustrating movement of the entire subject portion 762, according to one embodiment. As shown, the user need not necessarily move the first focus marker 752 and/or the second focus marker 754, but may instead elect to move the entire subject portion 762. As shown in FIG. 14A, this may be done by clicking on the subject portion 762 and dragging to the left or right, to move the subject portion 762 to a new position, as indicated by the arrows 1420. Alternatively, as shown in FIG. 14B, the user may click on the focus slider 750 (for example, anywhere on the focus slider 750 except on the first focus marker 752 or the second focus marker 754) and dragging to the left or right, as indicated by the arrows 1470, to cause subject portion 762 to move continuously to the left or right, respectively, until the user stops dragging.


The result may be motion of the entire subject portion 762 to the left or right. The subject portion 762 may remain the same size, but the foreground portion 764 may expand while the background portion 766 contracts, or vice versa. The first focus marker 752 and the second focus marker 754 may both move to the left or right, representing simultaneous reduction or increase of the first focus depth 570 and the second focus depth 580.


The user may even move one or both of the first focus marker 752 and the second focus marker 754 to the left or right, off the end of the focus slider 750. The result may be elimination of one of the foreground portion 764 and the background portion 766 (and thus elimination of one of the foreground portion 714 and the background portion 716 of the image 710) if only one of the first focus marker 752 and the second focus marker 754 is moved off the end of the focus slider 750. If the first focus marker 752 and the second focus marker 754 are both moved off the end of the focus slider 750, the result may also be elimination of the subject portion 762 (and thence, the subject portion 712 of the image 710) as will be shown in FIG. 16B.



FIGS. 15A and 15B are screenshot diagrams 1500, 1550 depicting the focus spread toolbox 730 of the user interface of FIG. 7, before and after clicking on the focus slider 750, according to one embodiment. If the user clicks or taps (but does not hold) the focus slider 750 at a location 1570, the subject portion 762 may be moved to the location 1570 of the click or tap. Thus, the user may easily reposition the first focus marker 752 and the second focus marker 754. This method may be used in place of clicking and dragging the subject portion 762 or the focus slider 750 as described in connection with FIGS. 14A and 14B.



FIGS. 16A and 16B are screenshot diagrams 1600, 1650 depicting the focus spread toolbox 730 of the user interface of FIG. 7, before and after clicking and dragging on the focus slider 750 to move subject portion 762 off of the focus slider 750 entirely, according to one embodiment. In FIG. 16A, the user may click on the focus slider 750 and drag leftward in the direction of the arrow 1660 to move the subject portion 762 to the left, as set forth in FIG. 14. If the user continues the drag operation, the subject portion 762 continues to move leftward until the first focus marker 752 and the second focus marker 754 have both passed across the left end of the focus slider 750. The resulting view is shown in FIG. 16B.


In FIG. 16B, the first focus marker 752, the second focus marker 754, the subject portion 762, and the foreground portion 764 have all been moved across the left edge of the focus slider 750. An arrow 1670 may be shown at the left edge of the focus slider 750 to indicate that the focus spread is past the left edge of the focus slider 750.


The result of the configuration of FIG. 16B may be that the entire image 710 is part of the background portion 766. Blurring may be applied to the entire image 710, with increasing blurring with increasing distance from the camera. The user may retrieve the first focus marker 752, the second focus marker 754, the subject portion 762, and the foreground portion 764 by clicking on the focus slider 750 and dragging to the right, until they are again visible. Alternatively, the user may click on a location within the focus slider 750 to cause the subject portion 762 to move to that location, as described above in connection with FIG. 15B.



FIGS. 17 through 29 are examples of depth-based blurring of a different light-field image. These drawings illustrate the use of different features and procedures, per the description below.



FIG. 17 is a screenshot diagram 1700 depicting an exemplary user interface for initiation of depth-based image processing, showing an exemplary image 1710, according to another embodiment. The user interface of FIG. 17 may be similar to that of FIG. 7; accordingly, the user interface of FIG. 17 may have an editing pane 720 with components that are similar to those of the editing pane 720 of FIG. 7, and therefore are numbered with the same numerals used in FIG. 7.


As shown, the image 1710 is of a chessboard with chess pieces. In FIG. 17, the focus is set in the middle of the refocusable range from the original image capture. Thus, the extent to which the image 1710 is focused (or conversely, blurred) varies among the pieces on the chessboard. The pieces vary in distance from the camera; accordingly, use of a single focus depth results in pieces that are nearer to or further from the focus depth appearing out-of-focus, or blurred.



FIG. 18 is a screenshot diagram 1800 depicting the exemplary user interface of FIG. 17, with the focus spread overlay toggled to “On,” according to one embodiment. This selection may be made in the depth map toolbox 780 of the editing pane 720. The plane of focus is visible as a sharp transition from the blue to orange hashing in the overlay on the image. There is currently no focus spread region which is in focus (and hence, no subject portion 762 visible on the focus slider 750 of the toolbox 730). Rather, focus may be limited to a plane at a generally uniform depth in the image 1710.



FIG. 19 is a screenshot diagram 1900 depicting the exemplary user interface of FIG. 17, after the user has moved the first focus marker 752 and the second focus marker 754 apart, according to one embodiment. This may define a subject portion 762 on the focus slider 750, as in FIG. 7. The subject portion 762 may correspond to a broader region (i.e., more than a single depth plane) of the image 1710 that is now in focus. Here, the focus spread overlay is toggled “On” via the depth map toolbox 780. The spread of the in-focus region is visible as a transparent region between the blue and orange overlay hashing on the image 1710.



FIG. 20 is a screenshot diagram 2000 depicting the exemplary user interface of FIG. 17, after the user has designated a location 2010 in the image 1710 to refocus the image 1710 to the location 2010. The in-focus region may jump to the location 2010 on the image 1710 that the user has clicked, tapped, or otherwise designated. Here, the user has clicked close to or on the pawn that is second-to-nearest to the camera. Accordingly, this pawn (and the rook beside it, which is at approximately the same depth) may both be in focus.



FIG. 21 is a screenshot diagram 2100 depicting the exemplary user interface of FIG. 17 after user designation of location 2010 on the image 1710 as in FIG. 20, and after the focus spread overlay has been enabled. The in-focus region is indicated where the user has clicked on the image close to or on the pawn that is second-to-nearest to the camera).



FIG. 22 is a screenshot diagram 2200 depicting the exemplary user interface of FIG. 17 after the user has designated a different location 2210 on the image 1710 to refocus the image 1710 to that location. The in-focus region may again jump to the location 2210 on the image 1710 that the user has clicked, tapped, or otherwise designated. Here, the user has clicked close to the pawn that is the third-to-furthest from the camera. Accordingly, this pawn, and adjacent pieces at similar depth levels, are in focus.



FIG. 23 is a screenshot diagram 2300 depicting the exemplary user interface of FIG. 17 after user designation of location 2210 on the image 1710 as in FIG. 22, and after the focus spread overlay has been enabled. The in-focus region is indicated at the location 2210 where the user has clicked on the image 1710 (close to the pawn that is the third-to-furthest from the camera).



FIG. 24 is a screenshot diagram 2400 depicting the exemplary user interface of FIG. 17 after modification of the tilt controls in the tilt toolbox 790 of the editing pane 720. More specifically, the tilt toolbox 790 may have a tilt slider 2410 and a rotation slider 2420 that can be used to orient the focus plane, which may be the plane at which the image 1710 is focused (or the plane at which focus of the image 1710 is centered, if the first focus marker 752 and the second focus marker 754 are spread apart to focus the image 1710 at a broader range than a single plane). The tilt slider 2410 may “tilt,” or rotate, the focus plane about an axis that can be oriented via adjustment of the rotation slider 2420. With the rotation slider 2420 centered, the axis of rotation about which the focus plane rotates with adjustment of the tilt slider 2410 may be horizontal.


In FIG. 24, the user has tilted the focus plane with the tilt slider 2410 to more closely match the uniform heights of the pawn faces on the chessboard. A subtle adjustment of the rotation, with the rotation slider 2420, orients the in-focus region around the center of the image 1710.



FIG. 25 is a screenshot diagram 2500 depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider 2410 and the rotation slider 2420 in FIG. 24, and after the focus spread overlay has been enabled. The in-focus region is indicated as the faces of the pawns.



FIG. 26 is a screenshot diagram 2600 depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider 2410 and the rotation slider 2420 in FIG. 24, and after the user has designated another different location on the image 1710 to refocus the image 1710 to that location. The tilted in-focus region jumps to where the user has clicked on the image 170. Here, the user has clicked on the face 2610 of the queen on the chessboard, resulting in the heads of the back row of chess pieces being generally in focus.



FIG. 27 is a screenshot diagram 2700 depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider 2410 and the rotation slider 2420 in FIG. 24 and designation of a new in-focus region as in FIG. 26, and after the focus spread overlay has been enabled. The in-focus region is indicated as the heads of the back row of chess pieces.



FIG. 28 is a screenshot diagram 2800 depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider 2410 and the rotation slider 2420 in FIG. 24, and after the user has designated another different location on the image 1710 to refocus the image 1710 to that location. The tilted in-focus region jumps to where the user has clicked on the image 170. Here, the user has clicked on the base of one of the pawns, resulting in the in-focus display of the checkerboard and the bases of all of the chess pieces.



FIG. 29 is a screenshot diagram 2900 depicting the exemplary user interface of FIG. 17 after user adjustment of the tilt slider 2410 and the rotation slider 2420 in FIG. 24 and designation of a new in-focus region in FIG. 28, and after the focus spread overlay has been enabled. The in-focus region is indicated as the checkerboard and the bases of all of the chess pieces.



FIGS. 7 through 29 are merely exemplary. Those of skill in the art will recognize that a wide variety of depth-based effects may be applied in addition to or in the alternative to blurring. Such effects may be applied according to a wide variety of functions, which may include linear and nonlinear functions. A few exemplary variations will be shown and described in connection with FIGS. 30A through 31B.


Variations


As indicated previously, various bokeh effects may be applied through the selection of a focus spread. The systems and methods set forth above for establishing a focus spread may be used to control the application of such bokeh effects. One exemplary bokeh effect is a blur shape, which may appear as a halo around a bright location in the blurred portion of an image. The system and method of the present disclosure may be used to apply such blur shapes. Exemplary blur shapes will be shown and described in connection with FIGS. 30A through 30D.



FIGS. 30A, 30B, 30C, and 30D are schematic block diagrams 3000, 3020, 3040, 3060 of various blur shapes that may be used to apply bokeh effects, according to exemplary embodiments. More specifically, FIG. 30A illustrates a circular shape 3010, which may simulate the blur shape that may be captured with the circular lens of a traditional camera. FIG. 30B illustrates a hexagonal shape 3030. FIG. 30C illustrates a star shape 3050, with four points. FIG. 30D illustrates a heart shape 3070.


These are merely examples of blur shapes that may be used for bokeh effects. In some embodiments, other blur shapes may be used, such as other polygonal shapes, ellipses, shapes with mixed curves and straight segments, and other fanciful shapes. If desired, an image may have more than one blur shape applied to it. Such different blur shapes may be applied based on depth (Z coordinate), horizontal or vertical location (X or Y coordinates), or other factors. In some embodiments, variable blur shapes may be used with variation based on distance from the focus spread.


Thus, for example, the near background (the region of the background portion 716 closest to the second focus depth 580) may have one shape, while the far background (the region of the background portion 716 furthest from the second focus depth 580) may have a different shape. The transition between the two shapes may be abrupt or smooth. If desired, a series of intermediate shapes may automatically be generated, and may be applied to provide a gradual transition between shapes with changing depth.


According to other alternatives, other factors such as the size, orientation, and/or positional offset of blur shapes may be varied with changes in depth. For example, a blur shape in the background portion 716 may be applied with a small size at maximum depth; the size of the blur shape may increase as the depth of objects in the image 710 approaches the second focus depth 580.



FIGS. 5A and 5B both represent blurring effects as linear functions of distance from the camera. In some embodiments, nonlinear functions may instead be applied. This concept will be shown and described in connection with FIGS. 31A and 31B.



FIGS. 31A and 31B are graphs 3100, 3150 illustrating linear and nonlinear application of blur effects, respectively, according to exemplary embodiments. Each of the graphs 3100, 3150 may have a horizontal axis 3110 that represents the distance of objects in the image from the camera, and a vertical axis 3120 that represents the blurriness of those objects. Each of the graphs 3100, 3150 may also have a focus range 3160, within which all objects are in focus. The focus range 3160 may extend from a first focus depth 3170 to a second focus depth 3180, like those of FIG. 5B.


In FIG. 31A, linear functions may be used to determine blurriness based on depth differential relative to the first focus depth 3170 and the second focus depth 3180. More particularly, a linear foreground function 3182 may be used to determine blurriness based on the depth differential between an object and the first focus depth 3170. A nonlinear background function 3184 may be used to determine blurriness based on a depth differential between an object and the second focus depth 3180. The linear foreground function 3182 and the nonlinear background function 3184 are, as linear functions, represented by straight lines with constant slopes.


Thus, the transition in application of blurring or other depth-based effects between any two points (for example, a first point 3186 and a second point 3188 on the nonlinear background function 3184) may vary with a linear relationship to depth (distance from the camera). The first point 3186 and the second point 3188 may represent different degrees of blurriness, or in alternative embodiments, different application of depth-based effects such as the use of different sizes or shapes of blur shapes.


In FIG. 31B, nonlinear functions may be used to determine blurriness based on depth differential relative to the first focus depth 3170 and the second focus depth 3180. More particularly, a nonlinear foreground function 3192 may be used to determine blurriness based on the depth differential between an object and the first focus depth 3170. A nonlinear background function 3194 may be used to determine blurriness based on a depth differential between an object and the second focus depth 3180. The nonlinear foreground function 3192 and the nonlinear background function 3194 are, as nonlinear functions, represented by lines with arbitrary, curvilinear shapes with varied slopes.


Thus, the transition in application of blurring or other depth-based effects between any two points may be variable, depending on the points selected. For example, a first point 3196 and a second point 3198 may represent different degrees of blurriness, or in alternative embodiments, different application of depth-based effects such as the use of different sizes or shapes of blur shapes. The transition in application of such effects between the first point 3196 and the second point 3198 may be variable with depth. As shown, the nonlinear background function 3194 need not continuously rise, but may fall as application of an effect is reversed with increasing depth, for some portion of the function.


In various embodiments, the user may have visibility to and/or control over the functions used to apply depth-based processing. A wide variety of user interfaces may be used to accomplish this. The user may select from a variety of pre-established linear and/or nonlinear functions, or may have the option to customize a function.


The above description and referenced drawings set forth particular details with respect to possible embodiments. Those of skill in the art will appreciate that the techniques described herein may be practiced in other embodiments. First, the particular naming of the components, capitalization of terms, the attributes, data structures, or any other programming or structural aspect is not mandatory or significant, and the mechanisms that implement the techniques described herein may have different names, formats, or protocols. Further, the system may be implemented via a combination of hardware and software, as described, or entirely in hardware elements, or entirely in software elements. Also, the particular division of functionality between the various system components described herein is merely exemplary, and not mandatory; functions performed by a single system component may instead be performed by multiple components, and functions performed by multiple components may instead be performed by a single component.


Reference in the specification to “one embodiment” or to “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.


Some embodiments may include a system or a method for performing the above-described techniques, either singly or in any combination. Other embodiments may include a computer program product comprising a non-transitory computer-readable storage medium and computer program code, encoded on the medium, for causing a processor in a computing device or other electronic device to perform the above-described techniques.


Some portions of the above are presented in terms of algorithms and symbolic representations of operations on data bits within a memory of a computing device. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self-consistent sequence of steps (instructions) leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical, magnetic or optical signals capable of being stored, transferred, combined, compared and otherwise manipulated. It is convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. Furthermore, it is also convenient at times, to refer to certain arrangements of steps requiring physical manipulations of physical quantities as modules or code devices, without loss of generality.


It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussion, it is appreciated that throughout the description, discussions utilizing terms such as “processing” or “computing” or “calculating” or “displaying” or “determining” or the like, refer to the action and processes of a computer system, or similar electronic computing module and/or device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system memories or registers or other such information storage, transmission or display devices.


Certain aspects include process steps and instructions described herein in the form of an algorithm. It should be noted that the process steps and instructions of described herein can be embodied in software, firmware and/or hardware, and when embodied in software, can be downloaded to reside on and be operated from different platforms used by a variety of operating systems.


Some embodiments relate to an apparatus for performing the operations described herein. This apparatus may be specially constructed for the required purposes, or it may comprise a general-purpose computing device selectively activated or reconfigured by a computer program stored in the computing device. Such a computer program may be stored in a computer readable storage medium, such as, but is not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, flash memory, solid state drives, magnetic or optical cards, application specific integrated circuits (ASICs), and/or any type of media suitable for storing electronic instructions, and each coupled to a computer system bus. Further, the computing devices referred to herein may include a single processor or may be architectures employing multiple processor designs for increased computing capability.


The algorithms and displays presented herein are not inherently related to any particular computing device, virtualized system, or other apparatus. Various general-purpose systems may also be used with programs in accordance with the teachings herein, or it may prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will be apparent from the description provided herein. In addition, the techniques set forth herein are not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the techniques described herein, and any references above to specific languages are provided for illustrative purposes only.


Accordingly, in various embodiments, the techniques described herein can be implemented as software, hardware, and/or other elements for controlling a computer system, computing device, or other electronic device, or any combination or plurality thereof. Such an electronic device can include, for example, a processor, an input device (such as a keyboard, mouse, touchpad, trackpad, joystick, trackball, microphone, and/or any combination thereof), an output device (such as a screen, speaker, and/or the like), memory, long-term storage (such as magnetic storage, optical storage, and/or the like), and/or network connectivity, according to techniques that are well known in the art. Such an electronic device may be portable or nonportable. Examples of electronic devices that may be used for implementing the techniques described herein include: a mobile phone, personal digital assistant, smartphone, kiosk, server computer, enterprise computing device, desktop computer, laptop computer, tablet computer, consumer electronic device, television, set-top box, or the like. An electronic device for implementing the techniques described herein may use any operating system such as, for example: Linux; Microsoft Windows, available from Microsoft Corporation of Redmond, Wash.; Mac OS X, available from Apple Inc. of Cupertino, Calif.; iOS, available from Apple Inc. of Cupertino, Calif.; Android, available from Google, Inc. of Mountain View, Calif.; and/or any other operating system that is adapted for use on the device.


In various embodiments, the techniques described herein can be implemented in a distributed processing environment, networked computing environment, or web-based computing environment. Elements can be implemented on client computing devices, servers, routers, and/or other network or non-network components. In some embodiments, the techniques described herein are implemented using a client/server architecture, wherein some components are implemented on one or more client computing devices and other components are implemented on one or more servers. In one embodiment, in the course of implementing the techniques of the present disclosure, client(s) request content from server(s), and server(s) return content in response to the requests. A browser may be installed at the client computing device for enabling such requests and responses, and for providing a user interface by which the user can initiate and control such interactions and view the presented content.


Any or all of the network components for implementing the described technology may, in some embodiments, be communicatively coupled with one another using any suitable electronic network, whether wired or wireless or any combination thereof, and using any suitable protocols for enabling such communication. One example of such a network is the Internet, although the techniques described herein can be implemented using other networks as well.


While a limited number of embodiments has been described herein, those skilled in the art, having benefit of the above description, will appreciate that other embodiments may be devised which do not depart from the scope of the claims. In addition, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, the disclosure is intended to be illustrative, but not limiting.

Claims
  • 1. A method for processing an image, the method comprising: in a data store, receiving the image;on a display device, displaying a range bar comprising a first slider and a second slider;in an input device, receiving a first user input that designates a first focus depth by detecting motion selecting to move the first slider along the range bar to a first location corresponding to the first focus depth;in the input device, receiving a second user input that designates a second focus depth different from the first focus depth by detecting motion selecting to move the second slider along the range bar to a second location corresponding to the second focus depth;in a processor, identifying one or more foreground portions of the image, wherein the one or more foreground portions have one or more foreground portion depths, each of which is less than the first focus depth;in the processor, identifying one or more background portions of the image, wherein the one or more background portions have one or more background portion depths, each of which is greater than the second focus depth;in the processor, applying blurring to the one or more foreground portions and to the one or more background portions to generate a processed image; andon the display device, displaying the processed image.
  • 2. The method of claim 1, further comprising, in the data store, receiving a depth map indicative of a plurality of depths at which a plurality of objects were disposed, relative to a camera used to capture the image, during capture of the image; wherein identifying the one or more foreground portions comprises determining, based on the depth map, that the one or more foreground portions have the one or more foreground portion depths;and wherein identifying the one or more background portions comprises determining, based on the depth map, that the one or more background portions have the one or more background portion depths.
  • 3. The method of claim 2, wherein the image comprises a light-field image captured with a light-field image capture device.
  • 4. The method of claim 1, further comprising, on the display device: displaying a graphical user interface comprising the first slider and the second slider;in response to receipt of the first user input, displaying motion of the first slider to the first location; andin response to receipt of the second user input, displaying motion of the second slider to the second location.
  • 5. The method of claim 1, wherein the first focus depth is less than the second focus depth such that one or more intermediate portions of the image have one or more intermediate portion depths that are greater than the first focus depth and less than the second focus depth; and wherein generating the processed image comprises rendering the one or more intermediate portions of the image without blurring.
  • 6. The method of claim 1, wherein the first focus depth is greater than the second focus depth such one or more of the one or more foreground portions of the image are also included in the one or more background portions of the image; and wherein generating the processed image comprises applying blurring to an entirety of the image.
  • 7. The method of claim 1, wherein applying the blurring to the one or more foreground portions and to the one or more background portions comprises applying a noncircular blur shape to the one or more foreground portions and to the one or more background portions.
  • 8. The method of claim 1, wherein applying the blurring to the one or more foreground portions and to the one or more background portions comprises: applying a first noncircular blur shape to one or more first subsets of the one or more foreground portions and the one or more background portions that are at a first depth; andapplying a second noncircular blur shape to one or more second subsets of the one or more foreground portions and the one or more background portions that are at a second depth different from the first depth.
  • 9. The method of claim 1, wherein applying the blurring to the one or more foreground portions and to the one or more background portions comprises applying the blurring to each pixel of a plurality of pixels of the image based, at least partially, on at least one of an X coordinate of the pixel, and a Y coordinate of the pixel.
  • 10. The method of claim 9, further comprising, in the input device, prior to applying the blurring to the one or more foreground portions and to the one or more background portions, receiving a third user input that designates a tilt angle at which a focus plane of the image is to be tilted; wherein applying the blurring to the one or more foreground portions and to the one or more background portions further comprises applying the blurring to portions of the image that are displaced from the focus plane.
  • 11. The method of claim 10, further comprising, in the input device, prior to applying the blurring to the one or more foreground portions and to the one or more background portions, receiving a fourth user input that designates a rotation angle at which the focus plane is to be rotated.
  • 12. A non-transitory computer-readable medium for processing an image, comprising instructions stored thereon, that when executed by a processor, perform the steps of: causing a data store to receive the image;causing a display device to display a range bar comprising a first slider and a second slider;causing an input device to receive a first user input that designates a first focus depth by detecting motion selecting to move the first slider along the range bar to a first location corresponding to the first focus depth;causing the input device to receive a second user input that designates a second focus depth different from the first focus depth by detecting motion selecting to move the second slider along the range bar to a second location corresponding to the second focus depth;identifying one or more foreground portions of the image, wherein the one or more foreground portions have one or more foreground portion depths, each of which is less than the first focus depth;identifying one or more background portions of the image, wherein the one or more background portions have one or more background portion depths, each of which is greater than the second focus depth;applying blurring to the one or more foreground portions and to the one or more background portions to generate a processed image; andcausing the display device to display the processed image.
  • 13. The non-transitory computer-readable medium of claim 12, further comprising instructions stored thereon, that when executed by a processor, cause the data store to receive a depth map indicative of a plurality of depths at which a plurality of objects were disposed, relative to a camera used to capture the image, during capture of the image; wherein identifying the one or more foreground portions comprises determining, based on the depth map, that the one or more foreground portions have the one or more foreground portion depths;and wherein identifying the one or more background portions comprises determining, based on the depth map, that the one or more background portions have the one or more background portion depths.
  • 14. The non-transitory computer-readable medium of claim 12, further comprising instructions stored thereon, that when executed by a processor, perform the steps of: causing the display device, in response to receipt of the first user input, to display motion of the first slider to a first location corresponding to the first focus depth; andcausing the display device, in response to receipt of the second user input, to display motion of the second slider to a second location corresponding to the second focus depth;wherein the input device comprises a pointing device.
  • 15. The non-transitory computer-readable medium of claim 12, wherein the first focus depth is less than the second focus depth such that one or more intermediate portions of the image have one or more intermediate portion depths that are greater than the first focus depth and less than the second focus depth; and wherein generating the processed image comprises rendering the one or more intermediate portions of the image without blurring.
  • 16. The non-transitory computer-readable medium of claim 12, wherein applying the blurring to the one or more foreground portions and to the one or more background portions comprises applying the blurring to each pixel of a plurality of pixels of the image based, at least partially, on at least one of an X coordinate of the pixel, and a Y coordinate of the pixel.
  • 17. The non-transitory computer-readable medium of claim 16, further comprising instructions stored thereon, that when executed by a processor, cause the input device, prior to applying the blurring to the one or more foreground portions and to the one or more background portions, to receive a third user input that designates a tilt angle at which a focus plane of the image is to be tilted; wherein applying the blurring to the one or more foreground portions and to the one or more background portions further comprises applying the blurring to portions of the image that are displaced from the focus plane.
  • 18. A system for processing an image, the system comprising: a data store configured to receive the image;a display device, communicatively coupled to a processor, configured to display a range bar comprising a first slider on the range bar and a second slider on the range bar;an input device configured to: receive a first user input that designates a first focus depth by detecting motion selecting to move the first slider along the range bar to a first location corresponding to the first focus depth; andreceive a second user input that designates a second focus depth different from the first focus depth by detecting motion selecting to move the second slider along the range bar to a second location;wherein the processor is configured to: identify one or more foreground portions of the image, wherein the one or more foreground portions have one or more foreground portion depths, each of which is less than the first focus depth;identify one or more background portions of the image, wherein the one or more background portions have one or more background portion depths, each of which is greater than the second focus depth; andapply blurring to the one or more foreground portions and to the one or more background portions to generate a processed image; andwherein the display device is further configured to display the processed image.
  • 19. The system of claim 18, wherein the data store is further configured to receive a depth map indicative of a plurality of depths at which a plurality of objects were disposed, relative to a camera used to capture the image, during capture of the image; wherein the processor is further configured to identify the one or more foreground portions by determining, based on the depth map, that the one or more foreground portions have the one or more foreground portion depths;and wherein the processor is further configured to identify the one or more background portions by determining, based on the depth map, that the one or more background portions have the one or more background portion depths.
  • 20. The system of claim 18, wherein the display device is further configured to: in response to receipt of the first user input, display motion of the first slider to the first location; andin response to receipt of the second user input, display motion of the second slider to the second location;wherein the input device comprises a pointing device.
  • 21. The system of claim 18, wherein the first focus depth is less than the second focus depth such that one or more intermediate portions of the image have one or more intermediate portion depths that are greater than the first focus depth and less than the second focus depth; and wherein the processor is further configured to generate the processed image by rendering the one or more intermediate portions of the image without blurring.
  • 22. The system of claim 18, wherein the processor is further configured to apply the blurring to the one or more foreground portions and to the one or more background portions by applying the blurring to each pixel of a plurality of pixels of the image based, at least partially, on at least one of an X coordinate of the pixel, and a Y coordinate of the pixel.
  • 23. The system of claim 22, wherein the input device is further configured, prior to application of the blurring to the one or more foreground portions and to the one or more background portions, to receive a third user input that designates a tilt angle at which a focus plane of the image is to be tilted; wherein the processor is further configured to apply the blurring to the one or more foreground portions and to the one or more background portions by applying the blurring to portions of the image that are displaced from the focus plane.
  • 24. A method for processing an image, the method comprising: in a data store, receiving the image;in an input device, receiving a first user input that designates a first focus depth;in the input device, receiving a second user input that designates a second focus depth different from the first focus depth;in a processor, identifying one or more foreground portions of the image, wherein the one or more foreground portions have one or more foreground portion depths, each of which is less than the first focus depth;in the processor, identifying one or more background portions of the image, wherein the one or more background portions have one or more background portion depths, each of which is greater than the second focus depth, wherein the first focus depth is greater than the second focus depth such one or more of the one or more foreground portions of the image are also included in the one or more background portions of the image;in the processor, applying blurring to an entirety of the image to generate a processed image; andon a display device, displaying the processed image.
  • 25. The method of claim 24, further comprising, on the display device: displaying a graphical user interface comprising a first element and a second element;in response to receipt of the first user input, displaying motion of the first element to a first location corresponding to the first focus depth; andin response to receipt of the second user input, displaying motion of the second element to a second location corresponding to the second focus depth.
  • 26. The method of claim 25, wherein displaying the graphical user interface comprises displaying a range bar; wherein the first element comprises a first slider on the range bar;wherein the second element comprises a second slider on the range bar;wherein the input device comprises a pointing device;wherein receiving the first user input comprises, with the pointing device, detecting motion selecting to move the first slider along the range bar to the first location;and wherein receiving the second user input comprises, with the pointing device, detecting motion selecting to move the second slider along the range bar to the second location.
  • 27. A method for processing an image, the method comprising: in a data store, receiving the image;in an input device, receiving a first user input that designates a first focus depth;in the input device, receiving a second user input that designates a second focus depth different from the first focus depth;in a processor, identifying one or more foreground portions of the image, wherein the one or more foreground portions have one or more foreground portion depths, each of which is less than the first focus depth;in the processor, identifying one or more background portions of the image, wherein the one or more background portions have one or more background portion depths, each of which is greater than the second focus depth;in the processor, generating a processed image by applying a first noncircular blur shape to one or more first subsets of the one or more foreground portions and the one or more background portions that are at a first depth and applying a second noncircular blur shape to one or more second subsets of the one or more foreground portions and the one or more background portions that are at a second depth different from the first depth; andon a display device, displaying the processed image.
  • 28. The method of claim 27, further comprising, in the data store, receiving a depth map indicative of a plurality of depths at which a plurality of objects were disposed, relative to a camera used to capture the image, during capture of the image; wherein identifying the one or more foreground portions comprises determining, based on the depth map, that the one or more foreground portions have the one or more foreground portion depths;and wherein identifying the one or more background portions comprises determining, based on the depth map, that the one or more background portions have the one or more background portion depths.
  • 29. The method of claim 27, wherein the first focus depth is less than the second focus depth such that one or more intermediate portions of the image have one or more intermediate portion depths that are greater than the first focus depth and less than the second focus depth; and wherein generating the processed image comprises rendering the one or more intermediate portions of the image without blurring.
  • 30. The method of claim 27, further comprising, on the display device: displaying a graphical user interface comprising a first element and a second element;in response to receipt of the first user input, displaying motion of the first element to a first location corresponding to the first focus depth; andin response to receipt of the second user input, displaying motion of the second element to a second location corresponding to the second focus depth;wherein the first element comprises a first slider on the range bar;wherein the second element comprises a second slider on the range bar;wherein the input device comprises a pointing device;wherein receiving the first user input comprises, with the pointing device, detecting motion selecting to move the first slider along the range bar to the first location;and wherein receiving the second user input comprises, with the pointing device, detecting motion selecting to move the second slider along the range bar to the second location.
  • 31. A system for processing an image, the system comprising: a data store configured to receive the image;an input device configured to: receive a first user input that designates a first focus depth; andreceive a second user input that designates a second focus depth different from the first focus depth;a processor, communicatively coupled to the data store and the input device, configured to: identify one or more foreground portions of the image, wherein the one or more foreground portions have one or more foreground portion depths, each of which is less than the first focus depth;identify one or more background portions of the image, wherein the one or more background portions have one or more background portion depths, each of which is greater than the second focus depth; andgenerate a processed image by applying a first noncircular blur shape to one or more first subsets of the one or more foreground portions and the one or more background portions that are at a first depth and applying a second noncircular blur shape to one or more second subsets of the one or more foreground portions and the one or more background portions that are at a second depth different from the first depth; anda display device, communicatively coupled to the processor, configured to display the processed image.
CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No. 14/871,533 for “Depth-Based Image Blurring”, filed Sep. 30, 2015, the disclosure of which is incorporated herein by reference in its entirety. The present application is a continuation-in-part of U.S. application Ser. No. 15/439,710 for “Depth-Assigned Content for Depth-Enhanced Virtual Reality Images”, filed Feb. 22, 2017, the disclosure of which is incorporated herein by reference in its entirety. U.S. application Ser. No. 15/439,710 is a continuation-in-part of U.S. Utility application Ser. No. 13/533,319 for “Depth-Assigned Content for Depth-Enhanced Pictures,” filed Jun. 26, 2012, the disclosure of which is incorporated herein by reference in its entirety. The present application is related to U.S. application Ser. No. 14/837,465 for “Depth-Based Application of Image Effects”, filed Aug. 27, 2015, the disclosure of which is incorporated herein by reference in its entirety. The present application is related to U.S. application Ser. No. 13/774,925 for “Compensating for Sensor Saturation and Microlens Modulation During Light-Field Image Processing”, filed Feb. 22, 2013, the disclosure of which is incorporated herein by reference in its entirety. The present application is related to U.S. Utility application Ser. No. 13/774,971 for “Compensating for Variation in Microlens Position During Light-Field Image Processing”, filed on Feb. 22, 2013, issued on Sep. 9, 2014 as U.S. Pat. No. 8,831,377, the disclosure of which is incorporated herein by reference in its entirety. The present application is related to U.S. Utility application Ser. No. 13/774,986 for “Light-Field Processing and Analysis, Camera Control, and User Interfaces and Interaction on Light-Field Capture Devices”, filed on Feb. 22, 2013, issued on Mar. 31, 2015 as U.S. Pat. No. 8,995,785, the disclosure of which is incorporated herein by reference in its entirety. The present application is related to U.S. Utility application Ser. No. 13/688,026 for “Extended Depth of Field and Variable Center of Perspective in Light-Field Processing”, filed on Nov. 28, 2012, issued on Aug. 19, 2014 as U.S. Pat. No. 8,811,769, the disclosure of which is incorporated herein by reference in its entirety. The present application is related to U.S. Utility application Ser. No. 11/948,901 for “Interactive Refocusing of Electronic Images,”, filed Nov. 30, 2007, issued on Oct. 15, 2013 as U.S. Pat. No. 8,559,705, the disclosure of which is incorporated herein by reference in its entirety. The present application is related to U.S. Utility application Ser. No. 12/703,367 for “Light-field Camera Image, File and Configuration Data, and Method of Using, Storing and Communicating Same,”, filed Feb. 10, 2010, now abandoned, the disclosure of which is incorporated herein by reference in its entirety. The present application is related to U.S. Utility application Ser. No. 13/027,946 for “3D Light-field Cameras, Images and Files, and Methods of Using, Operating, Processing and Viewing Same”, filed on Feb. 15, 2011, issued on Jun. 10, 2014 as U.S. Pat. No. 8,749,620, the disclosure of which is incorporated herein by reference in its entirety. The present application is related to U.S. Utility application Ser. No. 13/155,882 for “Storage and Transmission of Pictures Including Multiple Frames,”, filed Jun. 8, 2011, issued on Dec. 9, 2014 as U.S. Pat. No. 8,908,058, the disclosure of which is incorporated herein by reference in its entirety.

US Referenced Citations (489)
Number Name Date Kind
725567 Ives Apr 1903 A
4383170 Takagi et al. May 1983 A
4661986 Adelson Apr 1987 A
4694185 Weiss Sep 1987 A
4920419 Easterly Apr 1990 A
5076687 Adelson Dec 1991 A
5077810 D'Luna Dec 1991 A
5251019 Moorman et al. Oct 1993 A
5282045 Mimura et al. Jan 1994 A
5499069 Griffith Mar 1996 A
5572034 Karellas Nov 1996 A
5610390 Miyano Mar 1997 A
5748371 Cathey, Jr. et al. May 1998 A
5757423 Tanaka et al. May 1998 A
5818525 Elabd Oct 1998 A
5835267 Mason et al. Nov 1998 A
5907619 Davis May 1999 A
5949433 Klotz Sep 1999 A
5974215 Bilbro et al. Oct 1999 A
6005936 Shimizu et al. Dec 1999 A
6021241 Bilbro et al. Feb 2000 A
6023523 Cohen et al. Feb 2000 A
6028606 Kolb et al. Feb 2000 A
6034690 Gallery et al. Mar 2000 A
6061083 Aritake et al. May 2000 A
6061400 Pearlstein et al. May 2000 A
6069565 Stern et al. May 2000 A
6075889 Hamilton, Jr. et al. Jun 2000 A
6091860 Dimitri Jul 2000 A
6097394 Levoy et al. Aug 2000 A
6115556 Reddington Sep 2000 A
6137100 Fossum et al. Oct 2000 A
6169285 Pertrillo et al. Jan 2001 B1
6201899 Bergen Mar 2001 B1
6221687 Abramovich Apr 2001 B1
6320979 Melen Nov 2001 B1
6424351 Bishop et al. Jul 2002 B1
6448544 Stanton et al. Sep 2002 B1
6466207 Gortler et al. Oct 2002 B1
6476805 Shum et al. Nov 2002 B1
6479827 Hamamoto et al. Nov 2002 B1
6483535 Tamburrino et al. Nov 2002 B1
6529265 Henningsen Mar 2003 B1
6577342 Webster Jun 2003 B1
6587147 Li Jul 2003 B1
6597859 Leinhardt et al. Jul 2003 B1
6606099 Yamada Aug 2003 B2
6674430 Kaufman et al. Jan 2004 B1
6687419 Atkin Feb 2004 B1
6768980 Meyer et al. Jul 2004 B1
6785667 Orbanes et al. Aug 2004 B2
6833865 Fuller et al. Dec 2004 B1
6842297 Dowski, Jr. et al. Jan 2005 B2
6900841 Mihara May 2005 B1
6924841 Jones Aug 2005 B2
6927922 George et al. Aug 2005 B2
7015954 Foote et al. Mar 2006 B1
7025515 Woods Apr 2006 B2
7034866 Colmenarez et al. Apr 2006 B1
7079698 Kobayashi Jul 2006 B2
7102666 Kanade et al. Sep 2006 B2
7164807 Morton Jan 2007 B2
7206022 Miller et al. Apr 2007 B2
7239345 Rogina Jul 2007 B1
7286295 Sweatt et al. Oct 2007 B1
7304670 Hussey et al. Dec 2007 B1
7329856 Ma et al. Feb 2008 B2
7336430 George Feb 2008 B2
7417670 Linzer et al. Aug 2008 B1
7469381 Ording Dec 2008 B2
7477304 Hu Jan 2009 B2
7587109 Reininger Sep 2009 B1
7620309 Georgiev Nov 2009 B2
7623726 Georgiev Nov 2009 B1
7633513 Kondo et al. Dec 2009 B2
7683951 Aotsuka Mar 2010 B2
7687757 Tseng et al. Mar 2010 B1
7723662 Levoy et al. May 2010 B2
7724952 Shum et al. May 2010 B2
7748022 Frazier Jun 2010 B1
7847825 Aoki et al. Dec 2010 B2
7936377 Friedhoff et al. May 2011 B2
7936392 Ng et al. May 2011 B2
7941634 Georgi May 2011 B2
7945653 Zuckerberg et al. May 2011 B2
7949252 Georgiev May 2011 B1
7982776 Dunki-Jacobs et al. Jul 2011 B2
8013904 Tan et al. Sep 2011 B2
8085391 Machida et al. Dec 2011 B2
8106856 Matas et al. Jan 2012 B2
8115814 Iwase et al. Feb 2012 B2
8155456 Babacan Apr 2012 B2
8155478 Vitsnudel et al. Apr 2012 B2
8189089 Georgiev et al. May 2012 B1
8228417 Georgiev et al. Jul 2012 B1
8248515 Ng et al. Aug 2012 B2
8259198 Cote et al. Sep 2012 B2
8264546 Witt Sep 2012 B2
8279325 Pitts et al. Oct 2012 B2
8289440 Knight et al. Oct 2012 B2
8290358 Georgiev Oct 2012 B1
8310554 Aggarwal et al. Nov 2012 B2
8315476 Georgiev et al. Nov 2012 B1
8345144 Georgiev et al. Jan 2013 B1
8400533 Szedo Mar 2013 B1
8400555 Georgiev et al. Mar 2013 B1
8427548 Lim et al. Apr 2013 B2
8442397 Kang et al. May 2013 B2
8446516 Pitts et al. May 2013 B2
8494304 Venable et al. Jul 2013 B2
8531581 Shroff Sep 2013 B2
8542933 Venkataraman et al. Sep 2013 B2
8559705 Ng Oct 2013 B2
8570426 Pitts Oct 2013 B2
8577216 Li et al. Nov 2013 B2
8581998 Dhno Nov 2013 B2
8589374 Chaudhri Nov 2013 B2
8593564 Border et al. Nov 2013 B2
8605199 Imai Dec 2013 B2
8614764 Pitts et al. Dec 2013 B2
8619082 Ciurea et al. Dec 2013 B1
8629930 Brueckner et al. Jan 2014 B2
8665440 Kompaniets et al. Mar 2014 B1
8675073 Aagaard et al. Mar 2014 B2
8724014 Ng et al. May 2014 B2
8736710 Spielberg May 2014 B2
8736751 Yun May 2014 B2
8749620 Pitts et al. Jun 2014 B1
8750509 Renkis Jun 2014 B2
8754829 Lapstun Jun 2014 B2
8760566 Pitts et al. Jun 2014 B2
8768102 Ng et al. Jul 2014 B1
8797321 Bertolami et al. Aug 2014 B1
8811769 Pitts et al. Aug 2014 B1
8831377 Pitts et al. Sep 2014 B2
8860856 Wetsztein et al. Oct 2014 B2
8879901 Caldwell et al. Nov 2014 B2
8903232 Caldwell Dec 2014 B1
8908058 Akeley et al. Dec 2014 B2
8948545 Akeley et al. Feb 2015 B2
8953882 Lim et al. Feb 2015 B2
8971625 Pitts et al. Mar 2015 B2
8976288 Ng et al. Mar 2015 B2
8988317 Liang et al. Mar 2015 B1
8995785 Knight et al. Mar 2015 B2
8997021 Liang et al. Mar 2015 B2
9001226 Ng et al. Apr 2015 B1
9013611 Szedo Apr 2015 B1
9106914 Doser Aug 2015 B2
9172853 Pitts et al. Oct 2015 B2
9184199 Pitts et al. Nov 2015 B2
9201193 Smith Dec 2015 B1
9210391 Mills Dec 2015 B1
9214013 Venkataraman et al. Dec 2015 B2
9294662 Vondran, Jr. et al. Mar 2016 B2
9300932 Knight et al. Mar 2016 B2
9305375 Akeley Apr 2016 B2
9305956 Pittes et al. Apr 2016 B2
9386288 Akeley et al. Jul 2016 B2
9392153 Myhre et al. Jul 2016 B2
9419049 Pitts et al. Aug 2016 B2
9467607 Ng et al. Oct 2016 B2
9497380 Jannard et al. Nov 2016 B1
9628684 Liang et al. Apr 2017 B2
9635332 Carroll et al. Apr 2017 B2
9639945 Oberheu et al. May 2017 B2
9647150 Blasco Claret May 2017 B2
9681069 El-Ghoroury et al. Jun 2017 B2
9774800 El-Ghoroury et al. Sep 2017 B2
9866810 Knight et al. Jan 2018 B2
9900510 Karafin et al. Feb 2018 B1
9979909 Kuang et al. May 2018 B2
20010048968 Cox et al. Dec 2001 A1
20010053202 Mazess et al. Dec 2001 A1
20020001395 Davis et al. Jan 2002 A1
20020015048 Nister Feb 2002 A1
20020061131 Sawhney May 2002 A1
20020109783 Hayashi et al. Aug 2002 A1
20020159030 Frey et al. Oct 2002 A1
20020199106 Hayashi Dec 2002 A1
20030081145 Seaman et al. May 2003 A1
20030103670 Schoelkopf et al. Jun 2003 A1
20030117511 Belz et al. Jun 2003 A1
20030123700 Wakao Jul 2003 A1
20030133018 Ziemkowski Jul 2003 A1
20030147252 Fioravanti Aug 2003 A1
20030156077 Balogh Aug 2003 A1
20040002179 Barton et al. Jan 2004 A1
20040012688 Tinnerinno et al. Jan 2004 A1
20040012689 Tinnerinno et al. Jan 2004 A1
20040101166 Williams et al. May 2004 A1
20040114176 Bodin et al. Jun 2004 A1
20040135780 Nims Jul 2004 A1
20040189686 Tanguay et al. Sep 2004 A1
20040257360 Sieckmann Dec 2004 A1
20050031203 Fukuda Feb 2005 A1
20050049500 Babu et al. Mar 2005 A1
20050052543 Li et al. Mar 2005 A1
20050080602 Snyder et al. Apr 2005 A1
20050162540 Yata Jul 2005 A1
20050212918 Serra et al. Sep 2005 A1
20050276441 Debevec Dec 2005 A1
20060023066 Li et al. Feb 2006 A1
20060050170 Tanaka Mar 2006 A1
20060056040 Lan Mar 2006 A1
20060056604 Sylthe et al. Mar 2006 A1
20060072175 Oshino Apr 2006 A1
20060082879 Miyoshi et al. Apr 2006 A1
20060130017 Cohen et al. Jun 2006 A1
20060208259 Jeon Sep 2006 A1
20060248348 Wakao et al. Nov 2006 A1
20060256226 Alon et al. Nov 2006 A1
20060274210 Kim Dec 2006 A1
20060285741 Subbarao Dec 2006 A1
20070008317 Lundstrom Jan 2007 A1
20070019883 Wong et al. Jan 2007 A1
20070030357 Levien et al. Feb 2007 A1
20070033588 Landsman Feb 2007 A1
20070052810 Monroe Mar 2007 A1
20070071316 Kubo Mar 2007 A1
20070081081 Cheng Apr 2007 A1
20070097206 Houvener May 2007 A1
20070103558 Cai et al. May 2007 A1
20070113198 Robertson et al. May 2007 A1
20070140676 Nakahara Jun 2007 A1
20070188613 Nobori et al. Aug 2007 A1
20070201853 Petschnigg Aug 2007 A1
20070229653 Matusik et al. Oct 2007 A1
20070230944 Georgiev Oct 2007 A1
20070269108 Steinberg et al. Nov 2007 A1
20080007626 Wernersson Jan 2008 A1
20080012988 Baharav et al. Jan 2008 A1
20080018668 Yamauchi Jan 2008 A1
20080031537 Gutkowicz-Krusin et al. Feb 2008 A1
20080049113 Hirai Feb 2008 A1
20080056569 Williams et al. Mar 2008 A1
20080122940 Mori May 2008 A1
20080129728 Satoshi Jun 2008 A1
20080144952 Chen et al. Jun 2008 A1
20080152215 Horie et al. Jun 2008 A1
20080168404 Ording Jul 2008 A1
20080180792 Georgiev Jul 2008 A1
20080187305 Raskar et al. Aug 2008 A1
20080193026 Horie et al. Aug 2008 A1
20080205871 Utagawa Aug 2008 A1
20080226274 Spielberg Sep 2008 A1
20080232680 Berestov et al. Sep 2008 A1
20080253652 Gupta et al. Oct 2008 A1
20080260291 Alakarhu et al. Oct 2008 A1
20080266688 Errando Smet et al. Oct 2008 A1
20080277566 Utagawa Nov 2008 A1
20080309813 Watanabe Dec 2008 A1
20080316301 Givon Dec 2008 A1
20090002365 Kurabayashi Jan 2009 A1
20090027542 Yamamoto et al. Jan 2009 A1
20090041381 Georgiev et al. Feb 2009 A1
20090041448 Georgiev et al. Feb 2009 A1
20090070710 Kagaya Mar 2009 A1
20090128658 Hayasaka et al. May 2009 A1
20090128669 Ng et al. May 2009 A1
20090135258 Nozaki May 2009 A1
20090140131 Utagawa Jun 2009 A1
20090102956 Georgiev Jul 2009 A1
20090185051 Sano Jul 2009 A1
20090185801 Georgiev et al. Jul 2009 A1
20090190022 Ichimura Jul 2009 A1
20090190024 Hayasaka et al. Jul 2009 A1
20090195689 Hwang et al. Aug 2009 A1
20090202235 Li et al. Aug 2009 A1
20090204813 Kwan Aug 2009 A1
20090273843 Raskar et al. Nov 2009 A1
20090295829 Georgiev et al. Dec 2009 A1
20090309973 Kogane Dec 2009 A1
20090310885 Tamaru Dec 2009 A1
20090321861 Oliver et al. Dec 2009 A1
20100003024 Agrawal et al. Jan 2010 A1
20100021001 Honsinger et al. Jan 2010 A1
20100026852 Ng et al. Feb 2010 A1
20100050120 Ohazama et al. Feb 2010 A1
20100060727 Steinberg et al. Mar 2010 A1
20100097444 Lablans Apr 2010 A1
20100103311 Makii Apr 2010 A1
20100107068 Butcher et al. Apr 2010 A1
20100111489 Presler May 2010 A1
20100123784 Ding et al. May 2010 A1
20100141780 Tan et al. Jun 2010 A1
20100141802 Knight Jun 2010 A1
20100142839 Lakus-Becker Jun 2010 A1
20100201789 Yahagi Aug 2010 A1
20100253782 Elazary Oct 2010 A1
20100265385 Knight et al. Oct 2010 A1
20100277629 Tanaka Nov 2010 A1
20100303288 Malone Dec 2010 A1
20100328485 Imamura et al. Dec 2010 A1
20110018903 Lapstun et al. Jan 2011 A1
20110019056 Hirsch et al. Jan 2011 A1
20110025827 Shpunt et al. Feb 2011 A1
20110050864 Bond Mar 2011 A1
20110050909 Ellenby Mar 2011 A1
20110069175 Mistretta et al. Mar 2011 A1
20110075729 Dane et al. Mar 2011 A1
20110090255 Wilson et al. Apr 2011 A1
20110123183 Adelsberger et al. May 2011 A1
20110129120 Chan Jun 2011 A1
20110129165 Lim et al. Jun 2011 A1
20110148764 Gao Jun 2011 A1
20110149074 Lee et al. Jun 2011 A1
20110169994 DiFrancesco et al. Jul 2011 A1
20110205384 Zamowski et al. Aug 2011 A1
20110221947 Awazu Sep 2011 A1
20110242334 Wilburn et al. Oct 2011 A1
20110242352 Hikosaka Oct 2011 A1
20110261164 Olesen et al. Oct 2011 A1
20110261205 Sun Oct 2011 A1
20110267263 Hinckley Nov 2011 A1
20110273466 Imai et al. Nov 2011 A1
20110133649 Bales et al. Dec 2011 A1
20110292258 Adler Dec 2011 A1
20110298960 Tan et al. Dec 2011 A1
20110304745 Wang et al. Dec 2011 A1
20110311046 Oka Dec 2011 A1
20110316968 Taguchi et al. Dec 2011 A1
20120014837 Fehr et al. Jan 2012 A1
20120050562 Perwass et al. Mar 2012 A1
20120056889 Carter et al. Mar 2012 A1
20120057040 Park et al. Mar 2012 A1
20120057806 Backlund et al. Mar 2012 A1
20120062755 Takahashi et al. Mar 2012 A1
20120132803 Hirato et al. May 2012 A1
20120133746 Bigioi et al. May 2012 A1
20120147205 Lelescu et al. Jun 2012 A1
20120176481 Lukk et al. Jul 2012 A1
20120188344 Imai Jul 2012 A1
20120201475 Carmel et al. Aug 2012 A1
20120206574 Shikata et al. Aug 2012 A1
20120218463 Benezra et al. Aug 2012 A1
20120224787 Imai Sep 2012 A1
20120229691 Hiasa et al. Sep 2012 A1
20120249529 Matsumoto et al. Oct 2012 A1
20120249550 Akeley Oct 2012 A1
20120249819 Imai Oct 2012 A1
20120251131 Henderson et al. Oct 2012 A1
20120257065 Velarde et al. Oct 2012 A1
20120257795 Kim et al. Oct 2012 A1
20120272271 Nishizawa et al. Oct 2012 A1
20120287246 Katayama Nov 2012 A1
20120287296 Fukui Nov 2012 A1
20120287329 Yahata Nov 2012 A1
20120293075 Engelen et al. Nov 2012 A1
20120300091 Shroff et al. Nov 2012 A1
20120237222 Ng et al. Dec 2012 A9
20120320239 Uehara Dec 2012 A1
20130002902 Ito Jan 2013 A1
20130002936 Hirama et al. Jan 2013 A1
20130021486 Richardson Jan 2013 A1
20130038696 Ding et al. Feb 2013 A1
20130041215 McDowall Feb 2013 A1
20130044290 Kawamura Feb 2013 A1
20130050546 Kano Feb 2013 A1
20130064453 Nagasaka et al. Mar 2013 A1
20130064532 Caldwell et al. Mar 2013 A1
20130070059 Kushida Mar 2013 A1
20130070060 Chatterjee et al. Mar 2013 A1
20130077880 Venkataraman et al. Mar 2013 A1
20130082905 Ranieri et al. Apr 2013 A1
20130088616 Ingrassia, Jr. Apr 2013 A1
20130093844 Shuto Apr 2013 A1
20130093859 Nakamura Apr 2013 A1
20130094101 Oguchi Apr 2013 A1
20130107085 Ng et al. May 2013 A1
20130113981 Knight et al. May 2013 A1
20130120356 Georgiev et al. May 2013 A1
20130120605 Georgiev et al. May 2013 A1
20130120636 Baer May 2013 A1
20130127901 Georgiev et al. May 2013 A1
20130128052 Catrein et al. May 2013 A1
20130128081 Georgiev et al. May 2013 A1
20130128087 Georgiev et al. May 2013 A1
20130135448 Nagumo et al. May 2013 A1
20130176481 Holmes et al. Jul 2013 A1
20130188068 Said Jul 2013 A1
20130215108 McMahon et al. Aug 2013 A1
20130215226 Chauvier et al. Aug 2013 A1
20130222656 Kaneko Aug 2013 A1
20130234935 Griffith Sep 2013 A1
20130242137 Kirkland Sep 2013 A1
20130258451 El-Ghoroury et al. Oct 2013 A1
20130262511 Kuffner et al. Oct 2013 A1
20130286236 Mankowski Oct 2013 A1
20130321574 Zhang et al. Dec 2013 A1
20130321581 El-Ghoroury Dec 2013 A1
20130321677 Cote et al. Dec 2013 A1
20130329068 Hamanaka Dec 2013 A1
20130329107 Burley et al. Dec 2013 A1
20130329132 Tico et al. Dec 2013 A1
20130335596 Demandoix et al. Dec 2013 A1
20130342526 Ng et al. Dec 2013 A1
20130342700 Kass Dec 2013 A1
20140002502 Han Jan 2014 A1
20140002699 Guan Jan 2014 A1
20140003719 Bai et al. Jan 2014 A1
20140009585 Campbell Jan 2014 A1
20140013273 Ng Jan 2014 A1
20140035959 Lapstun Feb 2014 A1
20140037280 Shirakawa Feb 2014 A1
20140049663 Ng et al. Feb 2014 A1
20140059462 Wernersson Feb 2014 A1
20140085282 Luebke et al. Mar 2014 A1
20140092424 Grosz Apr 2014 A1
20140098191 Rime et al. Apr 2014 A1
20140132741 Aagaard et al. May 2014 A1
20140133749 Kuo et al. May 2014 A1
20140139538 Barber et al. May 2014 A1
20140167196 Heimgartner et al. Jun 2014 A1
20140176540 Tosic et al. Jun 2014 A1
20140176592 Wilburn et al. Jun 2014 A1
20140176710 Brady Jun 2014 A1
20140177905 Grefalda Jun 2014 A1
20140184885 Tanaka et al. Jul 2014 A1
20140192208 Okincha Jul 2014 A1
20140193047 Grosz Jul 2014 A1
20140195921 Grosz Jul 2014 A1
20140204111 Vaidyanathan et al. Jul 2014 A1
20140211077 Ng et al. Jul 2014 A1
20140218540 Geiss et al. Aug 2014 A1
20140226038 Kimura Aug 2014 A1
20140240463 Pitts et al. Aug 2014 A1
20140240578 Fishman et al. Aug 2014 A1
20140267243 Venkataraman et al. Sep 2014 A1
20140267639 Tatsuta Sep 2014 A1
20140300753 Yin Oct 2014 A1
20140313350 Keelan Oct 2014 A1
20140313375 Milnar Oct 2014 A1
20140340390 Lanman et al. Nov 2014 A1
20140347540 Kang Nov 2014 A1
20140354863 Ahn et al. Dec 2014 A1
20140368494 Sakharnykh et al. Dec 2014 A1
20140368640 Strandemar et al. Dec 2014 A1
20150062178 Matas et al. Mar 2015 A1
20150062386 Sugawara Mar 2015 A1
20150092071 Meng et al. Apr 2015 A1
20150097985 Akeley Apr 2015 A1
20150104101 Bryant et al. Apr 2015 A1
20150189154 Laroia Jul 2015 A1
20150193937 Georgiev et al. Jul 2015 A1
20150206340 Munkberg et al. Jul 2015 A1
20150207990 Ford et al. Jul 2015 A1
20150237273 Sawadaishi Aug 2015 A1
20150279056 Akeley Oct 2015 A1
20150310592 Kano Oct 2015 A1
20150312553 Ng et al. Oct 2015 A1
20150312593 Akeley et al. Oct 2015 A1
20150370011 Ishihara Dec 2015 A1
20150370012 Ishihara Dec 2015 A1
20160029017 Liang Jan 2016 A1
20160142615 Liang May 2016 A1
20160155215 Suzuki Jun 2016 A1
20160165206 Huang et al. Jun 2016 A1
20160173844 Knight et al. Jun 2016 A1
20160191823 El-Ghoroury Jun 2016 A1
20160253837 Zhu et al. Sep 2016 A1
20160269620 Romanenko et al. Sep 2016 A1
20160307368 Akeley Oct 2016 A1
20160307372 Pitts et al. Oct 2016 A1
20160309065 Karafin et al. Oct 2016 A1
20160353026 Blonde et al. Dec 2016 A1
20160381348 Hayasaka Dec 2016 A1
20170059305 Nonn et al. Mar 2017 A1
20170067832 Ferrara, Jr. et al. Mar 2017 A1
20170091906 Liang et al. Mar 2017 A1
20170134639 Pitts May 2017 A1
20170139131 Karafin et al. May 2017 A1
20170237971 Pitts et al. Aug 2017 A1
20170243373 Bevensee et al. Aug 2017 A1
20170244948 Pang et al. Aug 2017 A1
20170256036 Song et al. Sep 2017 A1
20170263012 Sabater et al. Sep 2017 A1
20170318226 Jung Nov 2017 A1
20170358092 Bleibel et al. Dec 2017 A1
20170365068 Tan et al. Dec 2017 A1
20180012397 Carothers Jan 2018 A1
20180020204 Pang et al. Jan 2018 A1
20180033209 Akeley et al. Feb 2018 A1
20180034134 Pang et al. Feb 2018 A1
20180070066 Knight et al. Mar 2018 A1
20180070067 Knight et al. Mar 2018 A1
20180089903 Pang et al. Mar 2018 A1
20180097867 Pang et al. Apr 2018 A1
20180158198 Karnad Jun 2018 A1
Foreign Referenced Citations (12)
Number Date Country
101226292 Jul 2008 CN
101309359 Nov 2008 CN
19624421 Jan 1997 DE
2010020100 Jan 2010 JP
2011135170 Jul 2011 JP
2003052465 Jun 2003 WO
2006039486 Apr 2006 WO
2007092545 Aug 2007 WO
2007092581 Aug 2007 WO
2011010234 Mar 2011 WO
2011029209 Mar 2011 WO
2011081187 Jul 2011 WO
Non-Patent Literature Citations (170)
Entry
Agarwala, A., et al., “Interactive Digital Photomontage,” ACM Transactions on Graphics, Proceedings of SIGGRAPH 2004, vol. 32, No. 3, 2004.
Nguyen, Hubert. “Practical Post-Process Depth of Field.” GPU Gems 3. Upper Saddle River, NJ: Addison-Wesley, 2008.
Shade, Jonathan, et al., “Layered Depth Images”, SIGGRAPH 98, pp. 1-2.
Wikipedia—Lazy loading of image data: http://en.wikipedia.org/wiki/Lazy_loading. Retrieved Jan. 2013.
Wikipedia—Methods of Variable Bitrate Encoding: http://en.wikipedia.org/wiki/Variable_bitrate#Methods_of_VBR_encoding. Retrieved Jan. 2013.
Wikipedia—Portable Network Graphics format: http://en.wikipedia.org/wiki/Portable_Network_Graphics. Retrieved Jan. 2013.
Wikipedia—Unsharp Mask Technique: https://en.wikipedia.org/wiki/Unsharp_masking. Retrieved May 3, 2016.
Wilburn et al., “High Performance Imaging using Large Camera Arrays”, ACM Transactions on Graphics (TOG), vol. 24, Issue 3 (Jul. 2005), Proceedings of ACM SIGGRAPH 2005, pp. 765-776.
Wilburn, Bennett, et al., “High Speed Video Using a Dense Camera Array”, 2004.
Wilburn, Bennett, et al., “The Light Field Video Camera”, Proceedings of Media Processors 2002.
Williams, L. “Pyramidal Parametrics,” Computer Graphic (1983).
Winnemoller, H., et al., “Light Waving: Estimating Light Positions From Photographs Alone”, Eurographics 2005.
Wippermann, F. “Chirped Refractive Microlens Array,” Dissertation 2007.
Wuu, S., et al., “A Manufacturable Back-Side Illumination Technology Using Bulk Si Substrate for Advanced CMOS Image Sensors”, 2009 International Image Sensor Workshop, Bergen, Norway.
Wuu, S., et al., “BSI Technology with Bulk Si Wafer”, 2009 International Image Sensor Workshop, Bergen, Norway.
Xiao, Z. et al., “Aliasing Detection and Reduction in Plenoptic Imaging,” IEEE Conference on Computer Vision and Pattern Recognition; 2014.
Xu, Xin et al., “Robust Automatic Focus Algorithm for Low Contrast Images Using a New Contrast Measure,” Sensors 2011; 14 pages.
Zheng, C. et al., “Parallax Photography: Creating 3D Cinematic Effects from Stills”, Proceedings of Graphic Interface, 2009.
Zitnick, L. et al., “High-Quality Video View Interpolation Using a Layered Representation,” Aug. 2004; ACM Transactions on Graphics (TOG), Proceedings of ACM SIGGRAPH 2004; vol. 23, Issue 3; pp. 600-608.
Zoberbier, M., et al., “Wafer Cameras—Novel Fabrication and Packaging Technologies”, 2009 International Image Senor Workshop, Bergen, Norway, 5 pages.
Schirmacher, H. et al., “High-Quality Interactive Lumigraph Rendering Through Warping,” May 2000, Graphics Interface 2000.
Shreiner, OpenGL Programming Guide, 7th edition, Chapter 8, 2010.
Simpleviewer, “Tiltview”, http://simpleviewer.net/tiltviewer. Retrieved Jan. 2013.
Skodras, A. et al., “The JPEG 2000 Still Image Compression Standard,” Sep. 2001, IEEE Signal Processing Magazine, pp. 36-58.
Sloan, P., et al., “Precomputed radiance transfer for real-time rendering in dynamic, low-frequency lighting environments”, ACM Transactions on Graphics 21, 3, 527-536, 2002.
Snavely, Noah, et al., “Photo-tourism: Exploring Photo collections in 3D”, ACM Transactions on Graphics (SIGGRAPH Proceedings), 2006.
Sokolov, “Autostereoscopy and Integral Photography by Professor Lippmann's Method”, 1911, pp. 23-29.
Sony Corp, “Interchangeable Lens Digital Camera Handbook”, 2011.
Sony, Sony's First Curved Sensor Photo: http://www.engadget.com; Jul. 2014.
Stensvold, M., “Hybrid AF: A New Approach to Autofocus is Emerging for both Still and Video”, Digital Photo Magazine, Nov. 13, 2012.
Story, D., “The Future of Photography”, Optics Electronics, Oct. 2008.
Sun, Jian, et al., “Stereo Matching Using Belief Propagation”, 2002.
Tagging photos on Flickr, Facebook and other online photo sharing sites (see, for example, http://support.gnip.com/customer/portal/articles/809309-flickr-geo-photos-tag-search). Retrieved Jan. 2013.
Takahashi, Keita, et al., “All in-focus View Synthesis from Under-Sampled Light Fields”, ICAT 2003, Tokyo, Japan.
Tanida et al., “Thin observation module by bound optics (TOMBO): concept and experimental verification” Applied Optics 40, 11 (Apr. 10, 2001), pp. 1806-1813.
Tao, Michael, et al., “Depth from Combining Defocus and Correspondence Using Light-Field Cameras”, Dec. 2013.
Techcrunch, “Coolinis”, Retrieved Jan. 2013.
Teo, P., et al., “Efficient linear rendering for interactive light design”, Tech. Rep. STAN-CS-TN-97-60, 1998, Stanford University.
Teranishi, N. “Evolution of Optical Structure in Images Sensors,” Electron Devices Meeting (IEDM) 2012 IEEE International; Dec. 10-13, 2012.
U.S. Appl. No. 15/590,808, filed May 9, 2017 listing Alex Song et al. as inventors, entitled “Adaptive Control for Immersive Experience Delivery”.
U.S. Appl. No. 15/590,841, filed May 9, 2017 listing Kurt Akeley et al. as inventors, entitled “Vantage Generation and Interactive Playback”.
U.S. Appl. No. 15/590,951, filed May 9, 2017 listing Alex Song et al. as inventors, entitled “Wedge-Based Light-Field Video Capture”.
U.S. Appl. No. 15/605,037, filed May 25, 2017 listing Zejing Wang et al. as inventors, entitled “Multl-View Back-Projection to a Light-Field”.
U.S. Appl. No. 15/666,298, filed Aug. 1, 2017 listing Yonggang Ha et al. as inventors, entitled “Focal Reducer With Controlled Optical Properties for Interchangeable Lens Light-Field Camera”.
U.S. Appl. No. 15/703,553, filed Sep. 13, 2017 listing Jon Karafin et al. as inventors, entitled “4D Camera Tracking and Optical Stabilization”.
U.S. Appl. No. 15/864,938, filed Jan. 8, 2018 listing Jon Karafin et al. as inventors, entitled “Motion Blur for Light-Field Images”.
U.S. Appl. No. 15/874,723, filed Jan. 18, 2018 listing Mark Weir et al. as inventors, entitled “Multi-Camera Navigation Interface”.
U.S. Appl. No. 15/897,836, filed Feb. 15, 2018 listing Francois Bleibel et al. as inventors, entitled “Multi-View Contour Tracking”.
U.S. Appl. No. 15/897,942, filed Feb. 15, 2018 listing Francois Bleibel et al. as inventors, entitled “Multi-View Contour Tracking With Grabcut”.
U.S. Appl. No. 15/897,994, filed Feb. 15, 2018 listing Trevor Carothers et al. as inventors, entitled “Generation of Virtual Reality With 6 Degrees of Freesom From Limited Viewer Data”.
U.S. Appl. No. 15/944,551, filed Apr. 3, 2018 listing Zejing Wang et al. as inventors, entitled “Generating Dolly Zoom Effect Using Light Field Image Data”.
U.S. Appl. No. 15/967,076, filed Apr. 30, 2018 listing Jiantao Kuang et al. as inventors, entitled “Automatic Lens Flare Detection and Correction for Light-Field Images”.
Vaish et al., “Using plane + parallax for calibrating dense camera arrays”, In Proceedings CVPR 2004, pp. 2-9.
Vaish, V., et al., “Synthetic Aperture Focusing Using a Shear-Warp Factorization of the Viewing Transform,” Workshop on Advanced 3D Imaging for Safety and Security (in conjunction with CVPR 2005), 2005.
VR Playhouse, “The Surrogate,” http://www.vrplayhouse.com/the-surrogate.
Wanner, S. et al., “Globally Consistent Depth Labeling of 4D Light Fields,” IEEE Conference on Computer Vision and Pattern Recognition, 2012.
Wanner, S. et al., “Variational Light Field Analysis for Disparity Estimation and Super-Resolution,” IEEE Transacations on Pattern Analysis and Machine Intellegence, 2013.
Wenger, et al, “Performance Relighting and Reflectance Transformation with Time-Multiplexed Illumination”, Institute for Creative Technologies, SIGGRAPH 2005.
Wetzstein, Gordon, et al., “Sensor Saturation in Fourier Multiplexed Imaging”, IEEE Conference on Computer Vision and Pattern Recognition (2010).
Wikipedia—Adaptive Optics: http://en.wikipedia.org/wiki/adaptive_optics. Retrieved Feb. 2014.
Wikipedia—Autofocus systems and methods: http://en.wikipedia.org/wiki/Autofocus. Retrieved Jan. 2013.
Wikipedia—Bayer Filter: http:/en.wikipedia.org/wiki/Bayer_filter. Retrieved Jun. 20, 2013.
Wikipedia—Color Image Pipeline: http://en.wikipedia.org/wiki/color_image_pipeline. Retrieved Jan. 15, 2014.
Wikipedia—Compression standard JPEG XR: http://en.wikipedia.org/wiki/JPEG_XR. Retrieved Jan. 2013.
Wikipedia—CYGM Filter: http://en.wikipedia.org/wiki/CYGM_filter. Retrieved Jun. 20, 2013.
Wikipedia—Data overlay techniques for real-time visual feed. For example, heads-up displays: http://en.wikipedia.org/wiki/Head-up_display. Retrieved Jan. 2013.
Wikipedia—Exchangeable image file format: http://en.wikipedia.org/wiki/Exchangeable_image_file_format. Retrieved Jan. 2013.
Wikipedia—Expeed: http://en.wikipedia.org/wiki/EXPEED. Retrieved Jan. 15, 2014.
Wikipedia—Extensible Metadata Platform: http://en.wikipedia.org/wiki/Extensible_Metadata_Platform. Retrieved Jan. 2013.
Wikipedia—Key framing for video animation: http://en.wikipedia.org/wiki/Key_frame. Retrieved Jan. 2013.
Adelsberger, R. et al., “Spatially Adaptive Photographic Flash,” ETH Zurich, Department of Computer Science, Technical Report 612, 2008, pp. 1-12.
Adelson et al., “Single Lens Stereo with a Plenoptic Camera” IEEE Translation on Pattern Analysis and Machine Intelligence, Feb. 1992. vol. 14, No. 2, pp. 99-106.
Adelson, E. H., and Bergen, J. R. 1991. The plenoptic function and the elements of early vision. In Computational Models of Visual Processing, edited by Michael S. Landy and J. Anthony Movshon. Cambridge, Mass.: mit Press.
Adobe Systems Inc, “XMP Specification”, Sep. 2005.
Adobe, “Photoshop CS6 / in depth: Digital Negative (DNG)”, http://www.adobe.com/products/photoshop/extend.displayTab2html. Retrieved Jan. 2013.
Andreas Observatory, Spectrograph Manual: IV. Flat-Field Correction, Jul. 2006.
Apple, “Apple iPad: Photo Features on the iPad”, Retrieved Jan. 2013.
Bae, S., et al., “Defocus Magnification”, Computer Graphics Forum, vol. 26, Issue 3 (Proc. of Eurographics 2007), pp. 1-9.
Belhumeur, Peter et al., “The Bas-Relief Ambiguity”, International Journal of Computer Vision, 1997, pp. 1060-1066.
Belhumeur, Peter, et al., “The Bas-Relief Ambiguity”, International Journal of Computer Vision, 1999, pp. 33-44, revised version.
Bhat, P. et al. “GradientShop: A Gradient-Domain Optimization Framework for Image and Video Filtering,” SIGGRAPH 2010; 14 pages.
Bolles, R., et al., “Epipolar-Plane Image Analysis: An Approach to Determining Structure from Motion”, International Journal of Computer Vision, 1, 7-55 (1987).
Bourke, Paul, “Image filtering in the Frequency Domain,” pp. 1-9, Jun. 1998.
Canon, Canon Speedlite wireless flash system, User manual for Model 550EX, Sep. 1998.
Chai, Jin-Xang et al., “Plenoptic Sampling”, ACM SIGGRAPH 2000, Annual Conference Series, 2000, pp. 307-318.
Chen, S. et al., “A CMOS Image Sensor with On-Chip Image Compression Based on Predictive Boundary Adaptation and Memoryless QTD Algorithm,” Very Large Scalee Integration (VLSI) Systems, IEEE Transactions, vol. 19, Issue 4; Apr. 2011.
Chen, W., et al., “Light Field mapping: Efficient representation and hardware rendering of surface light fields”, ACM Transactions on Graphics 21, 3, 447-456, 2002.
Cohen, Noy et al., “Enhancing the performance of the light field microscope using wavefront coding,” Optics Express, vol. 22, issue 20; 2014.
Daly, D., “Microlens Arrays” Retrieved Jan. 2013.
Debevec, et al, “A Lighting Reproduction Approach to Live-Action Compoisting” Proceedings SIGGRAPH 2002.
Debevec, P., et al., “Acquiring the reflectance field of a human face”, SIGGRAPH 2000.
Debevec, P., et al., “Recovering high dynamic radiance maps from photographs”, SIGGRAPH 1997, 369-378.
Design of the xBox menu. Retrieved Jan. 2013.
Digital Photography Review, “Sony Announce new RGBE CCD,” Jul. 2003.
Dorsey, J., et al., “Design and simulation of opera light and projection effects”, in Computer Graphics (Proceedings of SIGGRAPH 91), vol. 25, 41-50.
Dorsey, J., et al., “Interactive design of complex time dependent lighting”, IEEE Computer Graphics and Applications 15, 2 (Mar. 1995), 26-36.
Dowski et al., “Wavefront coding: a modern method of achieving high performance and/or low cost imaging systems” SPIE Proceedings, vol. 3779, Jul. 1999, pp. 137-145.
Dowski, Jr. “Extended Depth of Field Through Wave-Front Coding,” Applied Optics, vol. 34, No. 11, Apr. 10, 1995; pp. 1859-1866.
Duparre, J. et al., “Micro-Optical Artificial Compound Eyes,” Institute of Physics Publishing, Apr. 2006.
Eisemann, Elmar, et al., “Flash Photography Enhancement via Intrinsic Relighting”, SIGGRAPH 2004.
Fattal, Raanan, et al., “Multiscale Shape and Detail Enhancement from Multi-light Image Collections”, SIGGRAPH 2007.
Fernando, Randima, “Depth of Field—A Survey of Techniques,” GPU Gems. Boston, MA; Addison-Wesley, 2004.
Fitzpatrick, Brad, “Camlistore”, Feb. 1, 2011.
Fujifilm, Super CCD EXR Sensor by Fujifilm, brochure reference No. EB-807E, 2008.
Georgiev, T. et al., “Reducing Plenoptic Camera Artifacts,” Computer Graphics Forum, vol. 29, No. 6, pp. 1955-1968; 2010.
Georgiev, T., et al., “Spatio-Angular Resolution Tradeoff in Integral Photography,” Proceedings of Eurographics Symposium on Rendering, 2006..
Georgiev, T., et al., “Suppersolution with Plenoptic 2.0 Cameras,” Optical Society of America 2009; pp. 1-3.
Georgiev, T., et al., “Unified Frequency Domain Analysis of Lightfield Cameras” (2008).
Georgiev, T., et al., Plenoptic Camera 2.0 (2008).
Girod, B., “Mobile Visual Search”, IEEE Signal Processing Magazine, Jul. 2011.
Gortler et al., “The lumigraph” SIGGRAPH 96, pp. 43-54.
Groen et al., “A Comparison of Different Focus Functions for Use in Autofocus Algorithms,” Cytometry 6:81-91, 1985.
Haeberli, Paul “A Multifocus Method for Controlling Depth of Field” GRAPHICA Obscura, 1994, pp. 1-3.
Heide, F. et al., “High-Quality Computational Imaging Through Simple Lenses,” ACM Transactions on Graphics, SIGGRAPH 2013; pp. 1-7.
Heidelberg Collaboratory for Image Processing, “Consistent Depth Estimation in a 4D Light Field,” May 2013.
Hirigoyen, F., et al., “1.1 um Backside Imager vs. Frontside Image: an optics-dedicated FDTD approach”, IEEE 2009 International Image Sensor Workshop.
Huang, Fu-Chung et al., “Eyeglasses-free Display: Towards Correcting Visual Aberrations with Computational Light Field Displays,” ACM Transaction on Graphics, Aug. 2014, pp. 1-12.
Isaksen, A., et al., “Dynamically Reparameterized Light Fields,” SIGGRAPH 2000, pp. 297-306.
Ives H., “Optical properties of a Lippman lenticulated sheet,” J. Opt. Soc. Am. 21, 171 (1931).
Ives, H. “Parallax Panoramagrams Made with a Large Diameter Lens”, Journal of the Optical Society of America; 1930.
Jackson et al., “Selection of a Convolution Function for Fourier Inversion Using Gridding” IEEE Transactions on Medical Imaging, Sep. 1991, vol. 10, No. 3, pp. 473-478.
Kautz, J., et al., “Fast arbitrary BRDF shading for low-frequency lighting using spherical harmonics”, in Eurographic Rendering Workshop 2002, 291-296.
Koltun, et al., “Virtual Occluders: An Efficient Interediate PVS Representation”, Rendering Techniques 2000: Proc. 11th Eurographics Workshop Rendering, pp. 59-70, Jun. 2000.
Kopf, J., et al., Deep Photo: Model-Based Photograph Enhancement and Viewing, SIGGRAPH Asia 2008.
Lehtinen, J., et al. “Matrix radiance transfer”, in Symposium on Interactive 3D Graphics, 59-64, 2003.
Lesser, Michael, “Back-Side Illumination”, 2009.
Levin, A., et al., “Image and Depth from a Conventional Camera with a Coded Aperture”, SIGGRAPH 2007, pp. 1-9.
Levoy et al.,“Light Field Rendering” SIGGRAPH 96 Proceeding, 1996. pp. 31-42.
Levoy, “Light Fields and Computational Imaging” IEEE Computer Society, Aug. 2006, pp. 46-55.
Levoy, M. “Light Field Photography and Videography,” Oct. 18, 2005.
Levoy, M. “Stanford Light Field Microscope Project,” 2008; http://graphics.stanford.edu/projects/lfmicroscope/, 4 pages.
Levoy, M., “Autofocus: Contrast Detection”, http://graphics.stanford.edu/courses/cs178/applets/autofocusPD.html, pp. 1-3, 2010.
Levoy, M., “Autofocus: Phase Detection”, http://graphics.stanford.edu/courses/cs178/applets/autofocusPD.html, pp. 1-3, 2010.
Levoy, M., et al., “Light Field Microscopy,” ACM Transactions on Graphics, vol. 25, No. 3, Proceedings SIGGRAPH 2006.
Liang, Chia-Kai, et al., “Programmable Aperture Photography: Multiplexed Light Field Acquisition”, ACM SIGGRAPH, 2008.
Lippmann, “Reversible Prints”, Communication at the French Society of Physics, Journal of Physics, 7 , 4, Mar. 1908, pp. 821-825.
Lumsdaine et al., “Full Resolution Lightfield Rendering” Adobe Technical Report Jan. 2008, pp. 1-12.
Maeda, Y. et al., “A CMOS Image Sensor with Pseudorandom Pixel Placement for Clear Imaging,” 2009 International Symposium on Intelligent Signal Processing and Communication Systems, Dec. 2009.
Magnor, M. et al., “Model-Aided Coding of Multi-Viewpoint Image Data,” Proceedings IEEE Conference on Image Processing, ICIP-2000, Vancouver, Canada, Sep. 2000. https://graphics.tu-bs.de/static/people/magnor/publications/icip00.pdf.
Mallat, Stephane, “A Wavelet Tour of Signal Processing”, Academic Press 1998.
Malzbender, et al., “Polynomial Texture Maps”, Proceedings SIGGRAPH 2001.
Marshall, Richard J. et al., “Improving Depth Estimation from a Plenoptic Camera by Patterned Illumination,” Proc. of SPIE, vol. 9528, 2015, pp. 1-6.
Masselus, Vincent, et al., “Relighting with 4D Incident Light Fields”, SIGGRAPH 2003.
Meynants, G., et al., “Pixel Binning in CMOS Image Sensors,” Frontiers in Electronic Imaging Conference, 2009.
Moreno-Noguer, F. et al., “Active Refocusing of Images and Videos,” ACM Transactions on Graphics, Aug. 2007; pp. 1-9.
Munkberg, J. et al., “Layered Reconstruction for Defocus and Motion Blur” EGSR 2014, pp. 1-12.
Naemura et al., “3-D Computer Graphics based on Integral Photography” Optics Express, Feb. 12, 2001. vol. 8, No. 2, pp. 255-262.
Nakamura, J., “Image Sensors and Signal Processing for Digital Still Cameras” (Optical Science and Engineering), 2005.
National Instruments, “Anatomy of a Camera,” pp. 1-5, Sep. 6, 2006.
Nayar, Shree, et al., “Shape from Focus”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, No. 8, pp. 824-831, Aug. 1994.
Ng, R., et al. “Light Field Photography with a Hand-held Plenoptic Camera,” Stanford Technical Report, CSTR 2005-2, 2005.
Ng, R., et al., “All-Frequency Shadows Using Non-linear Wavelet Lighting Approximation. ACM Transactions on Graphics,” ACM Transactions on Graphics; Proceedings of SIGGRAPH 2003.
Ng, R., et al., “Triple Product Wavelet Integrals for All-Frequency Relighting”, ACM Transactions on Graphics (Proceedings of SIGGRAPH 2004).
Ng., R., “Fourier Slice Photography,” ACM Transactions on Graphics, Proceedings of SIGGRAPH 2005, vol. 24, No. 3, 2005, pp. 735-744.
Nimeroff, J., et al., “Efficient rendering of naturally illuminatied environments” in Fifth Eurographics Workshop on Rendering, 359-373, 1994.
Nokia, “City Lens”, May 2012.
Ogden, J., “Pyramid-Based Computer Graphics”, 1985.
Okano et al., “Three-dimensional video system based on integral photography” Optical Engineering, Jun. 1999. vol. 38, No. 6, pp. 1072-1077.
Orzan, Alexandrina, et al., “Diffusion Curves: A Vector Representation for Smooth-Shaded Images,” ACM Transactions on Graphics—Proceedings of SIGGRAPH 2008; vol. 27; 2008.
Pain, B., “Back-Side Illumination Technology for SOI-CMOS Image Sensors”, 2009.
Perez, Patrick et al., “Poisson Image Editing,” ACM Transactions on Graphics—Proceedings of ACM SIGGRAPH 2003; vol. 22, Issue 3; Jul. 2003; pp. 313-318.
Petschnigg, George, et al., “Digial Photography with Flash and No-Flash Image Pairs”, SIGGRAPH 2004.
Primesense, “The Primesense 3D Awareness Sensor”, 2007.
Ramamoorthi, R., et al, “Frequency space environment map rendering” ACM Transactions on Graphics (SIGGRAPH 2002 proceedings) 21, 3, 517-526.
Ramamoorthi, R., et al., “An efficient representation for irradiance environment maps”, in Proceedings of SIGGRAPH 2001, 497-500.
Raskar, Ramesh et al., “Glare Aware Photography: 4D Ray Sampling for Reducing Glare Effects of Camera Lenses,” ACM Transactions on Graphics—Proceedings of ACM SIGGRAPH, Aug. 2008; vol. 27, Issue 3; pp. 1-10.
Raskar, Ramesh et al., “Non-photorealistic Camera: Depth Edge Detection and Stylized Rendering using Multi-Flash Imaging”, SIGGRAPH 2004.
Raytrix, “Raytrix Lightfield Camera,” Raytrix GmbH, Germany 2012, pp. 1-35.
Roper Scientific, Germany “Fiber Optics,” 2012.
Scharstein, Daniel, et al., “High-Accuracy Stereo Depth Maps Using Structured Light,” CVPR'03 Proceedings of the 2003 IEEE Computer Society, pp. 195-202.
Related Publications (1)
Number Date Country
20180082405 A1 Mar 2018 US
Continuations (1)
Number Date Country
Parent 14871533 Sep 2015 US
Child 15824574 US
Continuation in Parts (2)
Number Date Country
Parent 15439710 Feb 2017 US
Child 14871533 US
Parent 13533319 Jun 2012 US
Child 15439710 US