The subject matter disclosed herein relates in general to image stitching and in particular to methods for stitching images taken with a small FOV camera in the presence of a large FOV image.
Multi-aperture cameras (or multi-cameras) are the standard for high-end mobile handheld devices (“mobile devices”, e.g. smartphone, tablet, etc.). A multi-camera usually comprises a wide field of view (FOVW) or “wide angle” camera (“Wide” camera or “W camera”), and one or more additional cameras, either with the same FOV, with a narrow FOV (Telephoto or “Tele” camera or “T” camera with Tele FOVT) or an ultra-wide camera with a FOVUW>FOVW (“UW camera”).
The Tele-Wide or Tele-Ultra-Wide multi-camera (which in the following may be referred to as a “Tele-Reference” multi-camera) combines benefits of both cameras to overcome shortcomings. It captures a large reference camera FOVR of the scene with the reference camera (“R camera”) that provides reference (R) images with a R camera resolution (“RESR”) and R signal-to-noise ratio (SNRR) and uses the higher Tele camera resolution (“REST”) and SNR (SNRT) to zoom into the scene with FOVT. However, as the Tele camera resolution increases, FOVT narrows, so that only a fraction of a scene can be captured.
A recent development is a scanning Tele camera that can scan a scene with its regular (native) FOVT, so that it effectively covers a scanning FOVT larger than native FOVT. A scanning Tele camera is described for example in co-owned U.S. Pat. No. 10,578,948.
There is need and it would be beneficial to have methods for using reference image (R image) data and Tele (T) image data to create a new image with a “new” field of view FOVN that fulfills FOVT<FOVN≤FOVR, wherein the image resolution of the new image RESN>RESR and/or wherein the SNR of the new image SNRN>SNRR.
In various embodiments, there are provided systems and methods for using reference image data and Tele image data to create a “new” image with a “new” field-of-view FOVN that fulfills FOVT<FOVN≤FOVR. The new image is a seamless, high resolution, large FOV image. The new image has a resolution RESN greater than RESR and/or a signal-to-noise ratio SNRN greater than SNRR. The new image can be a “super image” (“SI”), obtained by capturing and stitching two or more T images, or it can be a “super-wide image” (“SW”), obtained by capturing and using one or more T images to improve a R image or segments thereof with a super-resolution algorithm.
A SI comprises at least two high resolution Tele images and a R image (with RESR<REST) with a large FOV (e.g. FOVW or FOVUW) of the same scene, see
Other differences between a known panorama and a SI include the ability in the SI acquisition to scan automatically, thereby enabling to determine the scanning position and order of the Tele camera in an educated fashion; the ability to detect and correct bad images; and increased robustness due to higher overlap with the ground truth instead of overlap between different Tele images, which requires a smaller amount of images to cover a desired FOV, since the overlap size demand between the Tele images is reduced.
In various embodiments, there is provided a method, comprising: providing a folded Tele camera configured to scan and capture a plurality of Tele images, each captured image having a REST, a SNRT and a FOVT; obtaining and analyzing a R image with FOVR>FOVT and with an image resolution RESR<REST, and/or a R image with SNRR<SNRT; determining an order of one or more scanning FOVT positions for consecutive captures of the Tele images; capturing a Tele image at each respective scanning FOVT position; aligning the captured Tele images with segments of the R image to obtain aligned Tele images that are aligned with the R image; and using the aligned Tele images and the R image to create a new image having a field of view FOVN≤FOVR, wherein the image resolution of the new image RESN>RESR and/or wherein the SNR of the new image SNRN>SNRR.
In some embodiments, the R image is a Wide image having a FOVW>FOVT, the Wide image captured by a Wide camera included a multi-camera together with the folded Tele camera.
In some embodiments, the R image is an Ultra-Wide image having FOVUW>FOVW>FOVT, the Ultra-Wide image captured by an Ultra-Wide camera included in a multi-camera together with the folded Tele camera.
In some embodiments, a method further comprises aligning each Tele image with the R image immediately after its capture and prior to the capture of an immediately following Tele image, analyzing each Tele image for faults, and if faults are detected in the Tele image, re-capturing the Tele image at a same FOVT position, or, if faults are not detected in the Tele image, proceeding to capture an immediately following Tele image at a respective FOVT position.
In some embodiments, a method further comprises analyzing the aligned Tele images for faults, and if faults are detected in a particular Tele image, re-capturing the particular Tele image at a same FOVT position, or, if faults are not detected, using the aligned Tele images and the R image to create the new image.
In some embodiments, the folded Tele camera captures two or more Tele images at two or more respective FOVT positions within FOVR, and the aligned Tele images are composed to create a super image.
In some embodiments, the aligned Tele images and the R image are fed into an algorithm to create a super wide (SW) image having a field of view FOVSW, wherein a FOV segment within FOVR included in at least one FOVT of the captured Tele images has a field-of-view union-FOVT and wherein union-FOVT<FOVSW≤FOVR.
In some embodiments, the folded Tele camera is a multi-zoom Tele camera having different zoom states for capturing Tele images having different respective zoom factors.
In some embodiments, the obtaining of the R image includes obtaining the R image from the Internet, from a cloud database, or from an Internet of Things device.
In some embodiments, a video stream formed by a sequence of a plurality of new images is output instead of single new image.
In some embodiments, a user or an algorithm selects a size of FOVN and a position of FOVN within a scene included in FOVR.
In some embodiments, the analyzing of the R image includes using a saliency map of the R image for automatically selecting the scanning FOVT positions and/or automatically selecting the FOVN.
In some embodiments, the aligning of the captured Tele images to obtain a plurality of aligned Tele images includes localizing the T image data with respect to the R image data.
In some embodiments, the Tele camera has an effective focal length of 7-10 mm, of 10-20 mm, or of 20-40 mm.
In some embodiments, the determining an order of one or more scanning FOVT positions is performed so that each of the one and more Tele images exhibits a specific amount of natural Bokeh.
In some embodiments, the determining an order of one or more scanning FOVT positions is performed so that a composed new image covers a maximal FOV according to a mechanical limitation of the scanning.
In some embodiments, the determining an order of one or more scanning FOVT positions is performed so that the new image covers a region of interest selected by a user or by an algorithm.
In some embodiments, the determining an order of one or more scanning FOVT positions is performed so that each T images include scene segments having a specific depth range or include scene segments that do not exceed a specific depth threshold.
In some embodiments, the determining an order of one or more scanning FOVT positions is performed so that moving objects are captured first, and after the moving objects are captured, stationary objects are captured.
In some embodiments, the determining an order of one or more scanning FOVT positions is performed so that a desired coverage of FOVR with a plurality of FOVT is performed in a fastest manner.
In some embodiments, the determining an order of one or more scanning FOVT positions includes determining an order to follow a moving object with an object tracker.
In some embodiments, the determining an order of one or more scanning FOVT positions includes capturing an object in a Tele image with specific FOVT to improve RES or SNR of a similar object included in FOVN but not included in the specific FOVT.
In some embodiments, the determining an order of one or more scanning FOVT positions includes capturing a moving object with more than one FOVT at two significantly different points in time.
In some embodiments, FOVN>FOVT.
In some embodiments, the Tele images are additionally aligned with respect to each other to obtain aligned Tele images that are aligned with the R image and with each other.
In some embodiments, the R image includes a plurality of Wide images.
In some embodiments, the scanning Tele camera covers a scanning range larger than 25% of FOVW and/or FOVUW or larger than 50% of FOVW and/or FOVUW.
In some embodiments, the scanning Tele camera resolution REST>2×RESW and/or SNRT>2×SNRW, or REST>4×RESW and/or SNRT>4×SNRW.
In some embodiments, the faults are selected from the group consisting of motion blur, electronic noise, rolling shutter, defocus blur and incorrect image alignment or obstructions. In some embodiments, the faults are mechanical faults.
In some embodiments, the composing the aligned Tele images into the super image includes composing the aligned Tele images together with the R image into the super image.
In some embodiments, the determining an order of two or more FOVT positions is performed so that capturing a minimal number of T images is required.
In some embodiments, the determining an order of two or more FOVT positions is performed so that Tele images including specific scene characteristics within their respective FOVT s may be captured consecutively, and wherein the scene characteristics may be visual data such as texture or physical data such as brightness, depth or spectroscopic composition of a scene.
In some embodiments, the determining an order of two or more scanning FOVT positions is performed so that a moving object is removed from a scene included in FOVR.
In some embodiments, the determining an order of two or more scanning FOVT positions is performed to create a duplication of a moving object in a scene included in FOVR.
In some embodiments, the determining an order of two or more scanning FOVT positions is performed so that each Tele image overlaps with another Tele image.
In some embodiments, the determining an order of two or more scanning FOVT positions is performed so that one or more objects of interest are located in a center region of a FOVT and not in an overlap region.
In some embodiments, the multi-zoom Tele camera is a continuous-zoom Tele camera. In some embodiments, the multi-zoom Tele camera is a dual-zoom-state Tele camera.
In some embodiments, the R image is a Tele image having a first ZF (ZF1) and the Tele images that are captured consecutively according to the scanning order have a second zoom factor (ZF2), wherein ZF1≤1.25×ZF2.
A method disclosed herein is not limited to a specific multi-camera module, and could be used for any combination of cameras as long as the combination consists of at least one camera with some scanning capabilities, not limited to 2D scanning.
Non-limiting examples of embodiments disclosed herein are described below with reference to figures attached hereto that are listed following this paragraph. Identical structures, elements or parts that appear in more than one figure are generally labeled with a same numeral in all the figures in which they appear. If identical elements are shown but numbered in only one figure, it is assumed that they have the same number in all figures in which they appear. The drawings and descriptions are meant to illuminate and clarify embodiments disclosed herein and should not be considered limiting in any way. In the drawings:
Returning now to the figures,
In step 408, a subsequent Tele image is acquired (captured) using the scanning position selected or updated in step 406. For a SIM, the subsequently acquired Tele image is aligned with previously found Tele images that have some shared FOV and with the R image in step 410 to obtain an aligned Tele image. For a SWM, the subsequently acquired Tele image is aligned with the R image in step 410 to obtain an aligned Tele image. The aligned Tele image is analyzed for faults in step 412 and, based on the detected faults, a subsequent scanning position is updated by returning to step 406. Steps 406-412 are repeated until the desired coverage of the R image has been achieved. Afterwards, the SI or SW are composed as described in
In some embodiments, image composition step 414 may be performed after all the Tele images are acquired and aligned as described above. In other embodiments, image composition step 414 may be performed after each iteration of Tele image acquisition and image alignment steps 406-412, to perform “on the fly” blending with intermediate viable results. In such embodiments, a SI exists after each iteration of steps 406-412.
Steps 432-440 describe the process of aligning the T images captured in step 430 with the R image retrieved in step 422. Further details on the image alignment are described in
In step 442, the R image and the aligned T images are fed into a super-resolution algorithm. Relevant super-resolution algorithms are described for example in Daniel Glasner et al., “Super-Resolution from a Single Image”, ICCV, 2009, Tamar Rott Shaham et al., “SinGAN: Learning a Generative Model from a Single Natural Image”, ICCV, 2019, arXiv:1905.01164, or Assaf Shocher et al., “Zero-Shot Super-Resolution using Deep Internal Learning”, 2017, arXiv:1712.06087.
A new image having RESN>RESR and/or SNRN>SNRR is output in step 444. In general, FOVN is larger than the union of all FOVT s that are fed into the super-resolution algorithm in step 442, i.e. FOVN>union-FOVT. Union-FOVT represents the FOV within FOVR which is included in at least one FOVT of one of the T images captured in step 428.
The FOVT scanning may be performed by actuating (e.g. for rotation) one or more optical path folding elements (OPFEs) of the scanning Tele camera. Fast actuation may be desired. Actuation may be performed in 2-20 ms for scanning e.g. 2°-5° and in 10-70 ms for scanning 15-25°. A scanning Tele camera may have a maximal diagonal scanning range of 60°. “Maximal diagonal scanning range” is defined by the center of the FOV in the maximum state bottom-left of a center FOV and the center of the FOV in the maximum state top-right of a center FOV. For example and referring to FOV diagonal, a scanning T camera having FOVT=20° and 60° scanning range covers an overall FOV of 80°. A diagonal scanning range of 40° may cover around 60-100% of a FOVW. The scanning Tele camera may have an of EFL=7 mm-40 mm. Typical zoom factors (ZF) may be 2×-10× zoom with respect to a W camera hosted in the same mobile device, meaning that an image of a same object captured at a same distance is projected at a size 2×-10× larger on the image sensor of the T camera than on the W camera. Assuming that a same sensor is used in R camera and T camera, the image resolution scales linearly with the ZF. For same sensors, typically, REST>2× RESW. In some examples, REST>5× RESW.
It is noted that determining a scanning order includes determining the respective FOVT position, meaning that FOVT positions and their scanning order are determined.
In other embodiments for SIM and SWM, the scanning positions may be determined based on the maximal coverage of an object of interest or ROI as obtained from an algorithm, e.g. from a Saliency map, for example as described in “Salient Object Detection: A Discriminative Regional Feature Integration Approach” by Jiang et al. or as in “You Only Look Once: Unified, Real-Time Object Detection” by Redmon et al. The FOV of a SI or a SW may be selected based on the Saliency map.
In yet other embodiments for SIM, the scanning positions may be determined such that specific features within an ROI are located in a center region of a FOVT and not in an overlap region. A specific feature may be for example the face of a person. Locating specific features in a center region may avoid stitching artifacts in the SI's FOV segments where the ROI is located, e.g. by applying “stitching seams” in the FOV covered by the specific feature.
In yet other embodiments for SIM and SWM, scanning positions may be determined so that a minimal number of T image captures is required for a given selected ROI covering a particular FOV which is larger than FOVT, e.g. for reducing power consumption and capture time.
In yet other embodiments for SIM and SWM, a criterion for determining an order of scanning position may be based on artistic or visual effects such as e.g. a desired amount of natural Bokeh. The amount of natural Bokeh depends on differences in the object-lens distance of foreground objects (in-focus) and background objects (out-of-focus). A scanning position criterion may e.g. be an image background with uniform natural Bokeh.
In yet other embodiments for SIM and SWM, a criterion for determining an order of scanning position may be based on desired data for computational photography. Such data may be for example stereo image data including T image data and image data from the R image. From stereo image data of a single FOVT and the overlapping image FOV segment of the FOVR, a stereo depth map covering FOVT may be calculated as known in the art, e.g. by triangulation. The stereo depth map may enable application of artificial Bokeh algorithms to the R image or to the SI. In some embodiments, the SI output in step 414 may not be an image including visual data, but an output that includes stereo depth data.
In other embodiments, a scanning order criterion may include desired artistic SI effects. Such effects may be created by synchronizing T image capture and FOV scanning, wherein capture happens during FOV movement, so that a motion blur effect in the T image is achieved. For this, a scanning order criterion may be a desired amount of motion blur of a specific scene segment.
In yet other embodiments for SIM and SWM, a criterion for scanning position determination may be based on a depth estimation of the scene included in the R image. For example, one may select scanning positions so that single T images include scene segments having a specific depth range (i.e. a specific camera-object distance range) or include scene segments that do not exceed a specific depth threshold. In another example, one may select scanning positions so that single T images include ROIs covering a particular FOV size. As an example, a scanning order criterion may be to capture scene segments having similar depths or including ROIs of particular FOV sizes consecutively. This may be beneficial for a scanning camera that may have not one fixed FOV (i.e. zoom state) but different FOVs (zoom states). For fast SI or SW capture, one may prefer to capture FOV segments with identical zoom states consecutively (sequentially), as it may e.g. be desired to minimize number of (time-consuming) zoom state switches. As another example, a scanning order criterion may be to capture scene segments having similar depths consecutively, because this may minimize the amount of time required for re-focusing the T camera between single T image captures and may also facilitate the alignment of the T images.
In yet another embodiment for SIM and SWM, a scanning order criterion may be that T images comprising specific scene characteristics within their respective FOVT s may be captured consecutively. In some embodiments, T images with similar scene characteristics within their respective FOVT s may be captured consecutively. Scene characteristics may be visual data such as texture. Scene characteristics may be physical data such as brightness, depth or spectroscopic composition of a scene. A spectroscopic composition may be defined by the intensity values of all wavelengths present in the scene.
One can determine the order of capturing the T images such that the moving object will not appear in the scene at all, as illustrated in
The T scanning order (i.e. the scanning order criteria) may alternatively be based on camera or scene properties. In some embodiments, a scanning order criterion may be based on fast SI capture. In some embodiments, the SI output in step 414 or the SW output in step 444 may not be an image including visual data, but it may be an output including spectroscopic data, stereo depth data or other image data that is generated by computational photography or physical analysis.
In some embodiments, a plurality of sub-SIs that form a single SI may be captured in the FOV of a R image simultaneously, i.e. in a single capture process as described in
In contrast with SIM, in a SWM for increasing RES or SNR in a segment of FOVR one must not necessarily capture a T image having a FOVT that includes this very FOVR segment. It may be sufficient to capture a T image that includes similar features present in the same scene. As an example and with reference to
Furthermore, for SWM the T images must not necessarily be aligned with each other, but only with the R image. Therefore, the captured T images must not necessarily include an overlapping FOV, which is required for SIM.
There are several options for determining a T scanning order, as follows.
In another example, a T scanning order is determined so that a desired coverage of FOVR with a plurality of FOVT is performed in a fastest manner.
In yet another example and for a Tele camera which is a multi-zoom camera, a T scanning order is determined so that a desired coverage of FOVR with a desired zoom factor (ZF) is performed in a fastest manner. A user or an algorithm may select the desired ZF. One criterion for selecting the ZF may be a desired ratio of REST/RESR and/or of SNRT/SNRR, another criterion may be a desired FOVT. In some embodiments, the R image may be a Tele image which is captured with a first ZF (ZF1) and the Tele images that are captured consecutively according to the order have a second ZF (ZF2), wherein ZF1<ZF2, for example ZF1≤1.1×ZF2, ZF1≤1.25×ZF2, ZF1≤2×ZF2.
In yet another example and for a Tele camera which is a multi-zoom camera, a T scanning order is determined so that Tele images with a same ZF are captured consecutively. For example, first all Tele images with a particular first ZF (ZF1) are captured, and afterwards all Tele images with a particular second ZF (ZF2) are captured.
Some reasons may be related to scene characteristics that were not identified in the R image analysis. Consider for example a bright oscillating light source in FOVN. The light source may have been “Off” when the R image was captured, but it may have been “On” when the respective T image was captured, causing large differences in the T camera parameters deployed for this T image in contrast to prior or consecutive T images. In such a scenario re-capturing the T image with the light source “Off” may be desired.
An additional fault reason may relate to mechanical faults, e.g. the OPFE did not reach the desired location accurately, and therefore issues in the alignment of the image may occur and the image needs to be recaptured.
The influence of color correction step 1506 on the SI is shown in
Mobile device 1700 may further comprise a R (e.g. W or UW) camera module 1730 with a FOV larger than the FOV of camera module 1710. Camera module 1730 includes a second lens module 1732 that forms an image recorded by a second image sensor 1734. A second lens actuator 1736 may move lens module 1732 for focusing and/or OIS.
In some embodiments, first calibration data may be stored in a first memory 1722 of a camera module, e.g. in an EEPROM (electrically erasable programmable read only memory). In other embodiments, first calibration data may be stored in a third memory 1750 such as a NVM (non-volatile memory) of mobile device 1700. The first calibration data may comprise calibration data for calibration between sensors of R camera module 1730 and of T camera module 1710. In some embodiments, second calibration data may be stored in a second memory 1738. In some embodiments, the second calibration data may be stored in third memory 1750. The second calibration data may comprise calibration data between sensors of R camera module 1730 and T camera module 1710.
Mobile device 1700 may further comprise an application processor (AP) 1740. In use, AP 1740 may receive respective first and second (reference) image data from camera modules 1710 and 1730 and supply camera control signals to camera modules 1710 and 1730. In some embodiments, AP 1740 may receive first image data from camera module 1710 and R image data from third memory 1750. In other embodiments, AP 1740 may receive calibration data stored in a first memory located on camera module 1710 and in a second memory located in camera module 1730. In yet another embodiment, AP 1740 may receive R image data stored in third memory 1750. In yet another embodiment, AP 1740 may retrieve R images from an external database. AP 1740 includes an image analyzer 1742 for analyzing R images (e.g. for scene understanding and defining a Tele scanning order) and T images (e.g. for fault detection), a FOV scanner 1744 that calculates an OPFE control signal (e.g. for implementing a Tele scanning order) and an image generator 1744 for composing new images as outlined in steps 402-414 and in steps 1502-1510 (for SIM) and in steps 422-444 and in steps 1522-1528 (for SWM).
While this disclosure has been described in terms of certain embodiments and generally associated methods, alterations and permutations of the embodiments and methods will be apparent to those skilled in the art. The disclosure is to be understood as not limited by the specific embodiments described herein.
All references mentioned in this application are incorporated herein by reference in their entirety. It is emphasized that citation or identification of any reference in this application shall not be construed as an admission that such a reference is available or admitted as prior art.
This is a 371 application from international patent application PCT/IB2021/054070 filed May 12, 2021, and is related to and claims priority from U.S. Provisional Patent Application No. 63/026,097 filed May 17, 2020, which is incorporated herein by reference in its entirety.
Filing Document | Filing Date | Country | Kind |
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PCT/IB2021/054070 | 5/12/2021 | WO |
Publishing Document | Publishing Date | Country | Kind |
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WO2021/234515 | 11/25/2021 | WO | A |
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