Capturing and processing of images using camera array incorperating Bayer cameras having different fields of view

• US 9,749,547 B2
• Filed: 11/16/2015
• Issued: 08/29/2017
• Est. Priority Date: 05/20/2008
• Status: Active Grant

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: Fotonation Cayman Limited (Adeia Inc.)
• Inventors: Venkataraman, Kartik, Jabbi, Amandeep S., Mullis, Robert H., Duparre, Jacques, Hu, Shane Ching-Feng
• Primary Examiner(s): LAM, HUNG H
• Application Number:
  US14/943,009
• Publication Number:
  US 20160269650A1
• Time in Patent Office: 652 Days
• Field of Search: 3482221, 3482291, 3482312, 34823199, 348234, 348263, 348290, 348335, 348340, 348362
• CPC Class Codes: G02B 13/0015 characterised by the lens design
• CPC Class Codes: G02B 3/0056 arranged along two different directions in a plane, e.g. honeycomb arrangement of lenses G02B3/0043 takes precedence; miniaturised objectives for electronic devices employing wafer level optics G02B13/0085
• CPC Class Codes: G02B 3/0062 Stacked lens arrays, i.e. refractive surfaces arranged in at least two planes, without structurally separate optical elements in-between
• CPC Class Codes: G02B 5/20 Filters polarising elements G02B5/30
• CPC Class Codes: G02B 5/201 in the form of arrays
• CPC Class Codes: G06T 11/60 Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 19/20 Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/10052 Images from lightfield camera
• CPC Class Codes: G06T 2207/20221 Image fusion; Image merging
• CPC Class Codes: G06T 7/50 Depth or shape recovery
• CPC Class Codes: G06T 7/557 from light fields, e.g. from plenoptic cameras
• CPC Class Codes: H04N 13/128 Adjusting depth or disparity
• CPC Class Codes: H04N 13/239 using two 2D image sensors having a relative position equal to or related to the interocular distance H04N13/243 takes precedence
• CPC Class Codes: H04N 13/257 Colour aspects
• CPC Class Codes: H04N 2013/0081 Depth or disparity estimation from stereoscopic image signals
• CPC Class Codes: H04N 23/11 for generating image signals from visible and infrared light wavelengths
• CPC Class Codes: H04N 23/13 with multiple sensors
• CPC Class Codes: H04N 23/16 Optical arrangements associated therewith, e.g. for beam-splitting or for colour correction
• CPC Class Codes: H04N 23/45 : for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
• CPC Class Codes: H04N 23/54 : Mounting of pick-up tubes, electronic image sensors, deviation or focusing coils
• CPC Class Codes: H04N 23/55 : Optical parts specially adapted for electronic image sensors; Mounting thereof
• CPC Class Codes: H04N 23/60 : Control of cameras or camera modules
• CPC Class Codes: H04N 23/69 : Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming
• CPC Class Codes: H04N 23/698 : for achieving an enlarged field of view, e.g. panoramic image capture
• CPC Class Codes: H04N 23/88 : for colour balance, e.g. white-balance circuits or colour temperature control
• CPC Class Codes: H04N 23/90 : Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
• CPC Class Codes: H04N 23/951 : by using two or more images to influence resolution, frame rate or aspect ratio
• CPC Class Codes: H04N 25/131 : including elements passing infrared wavelengths
• CPC Class Codes: H04N 25/133 : including elements passing panchromatic light, e.g. filters passing white light
• CPC Class Codes: H04N 25/135 : based on four or more different wavelength filter elements
• CPC Class Codes: H04N 25/41 : Extracting pixel data from a plurality of image sensors simultaneously picking up an image, e.g. for increasing the field of view by combining the outputs of a plurality of sensors
• CPC Class Codes: H04N 25/48 : Increasing resolution by shifting the sensor relative to the scene
• CPC Class Codes: H04N 25/581 : acquired simultaneously
• CPC Class Codes: H04N 25/60 : Noise processing, e.g. detecting, correcting, reducing or removing noise
• CPC Class Codes: H04N 25/6153 : for colour signals
• CPC Class Codes: H04N 25/67 : applied to fixed-pattern noise, e.g. non-uniformity of response
• CPC Class Codes: H04N 25/705 : Pixels for depth measurement, e.g. RGBZ
• CPC Class Codes: H04N 25/79 : Arrangements of circuitry being divided between different or multiple substrates, chips or circuit boards, e.g. stacked image sensors
• CPC Class Codes: H04N 5/262 : Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
• CPC Class Codes: H04N 5/265 : Mixing

Abstract

Systems and methods for implementing array cameras configured to perform super-resolution processing to generate higher resolution super-resolved images using a plurality of captured images and lens stack arrays that can be utilized in array cameras are disclosed. An imaging device in accordance with one embodiment of the invention includes at least one imager array, and each imager in the array comprises a plurality of light sensing elements and a lens stack including at least one lens surface, where the lens stack is configured to form an image on the light sensing elements, control circuitry configured to capture images formed on the light sensing elements of each of the imagers, and a super-resolution processing module configured to generate at least one higher resolution super-resolved image using a plurality of the captured images.

Claims

1. A camera array, comprising:

a plurality of Bayer cameras capturing a plurality of images and forming at least three rows of cameras and at least three columns of cameras, where each camera includes separate optics and a plurality of sensor elements, and each camera is configured to independently capture an image of a scene;

wherein the optics of each camera are configured so that each camera has a field of view of the scene that is shifted with respect to the field-of-views of the other cameras;

wherein the plurality of images captured by the plurality of Bayer cameras include different occlusion sets, the occlusion set of a specific image captured by a given camera is the portion of a scene visible to a baseline camera from the plurality of cameras that is occluded from the view of the given camera; and

wherein the plurality of cameras includes a first camera that captures pixels around an edge of a foreground object that is visible to the baseline camera and is in the occlusion set of a second of the plurality of cameras.

2. The camera array of claim 1, wherein the plurality of images captured by the plurality of Bayer cameras are low resolution images, wherein the camera array further comprises a super-resolution processing module configured to generate at least one higher resolution super-resolved image using a plurality of the captured low resolution images by performing parallax detection to generate parallax information to align portions of the plurality of captured low resolution images.

3. The camera array of claim 2, further comprising:

an address conversion module configured to normalize the plurality of images captured by the plurality of Bayer cameras;

a parallax confirmation and measurement module configured to detect and meter parallax that includes ignoring pixels in the images that are in an exposed occlusion set; and

an image pixel correlation module configured to align portion of images captured by different cameras to compensate for parallax based upon the detected and metered parallax and calibration data;

wherein the super-resolution processing module is configured to generate a higher resolution image having a resolution that is higher than the resolutions of the plurality of images captured by the plurality of Bayer cameras.

4. The camera array of claim 3, wherein the parallax confirmation and measurement module is configured to detect and meter parallax by determining the parallax that yields the highest correlation between pixels from images captured by the plurality of Bayer cameras accounting for the positions of the cameras that captured the images.

5. The camera array of claim 4, wherein the parallax confirmation and measurement module is configured to determine the parallax that yields the highest correlation between pixels from images captured by performing pair-wise measurements to determine pixel correlation for different parallax-induced shifts.

6. The camera array of claim 5, wherein the parallax confirmation and measurement module is configured to determining the parallax that yields the highest correlations between pixels from images captured by keeping track of various pair-wise measurements and calculating a parallax that yields the highest correlation as the best least squares fit of the pair-wise measurements.

7. The camera array of claim 3, wherein the super-resolution processing module is configured to generate the at least one higher resolution super-resolved image by fusing the aligned image portions.

8. The camera array of claim 7, wherein the super-resolution processing module is further configured to interpolate luminance information from the aligned image portions to each grid point on the higher resolution image.

9. The camera array of claim 8, wherein the super-resolution processing module is further configured to perform super-resolution processing on the fused image portions to synthesize a super-resolution image.

10. The camera array of claim 1, further comprising a super-resolution module configured to generate a depth map using the parallax information.

11. The camera array of claim 1, wherein the camera array comprises an M×

N array of cameras, where N and M are both greater than 2.

12. The camera array of claim 1, further comprising control circuitry configured to control the imaging characteristics of each camera.

13. The camera array of claim 12, wherein imaging characteristics controlled by the control circuitry include exposure time, gain, and black level offset.

14. The camera array of claim 12, wherein the control circuitry is configured to trigger each of said cameras in accordance with a desired sequence.

15. The camera array of claim 12, wherein the control circuitry operates the cameras in a staggered sequence.

16. The camera array of claim 1, wherein at least two cameras have different focal lengths.

17. The camera array of claim 1, wherein the sensor elements in each of at least two cameras have different sizes.

18. The camera array of claim 1, wherein at least two cameras have different numbers of sensor elements.

19. The camera array of claim 1, wherein the camera array includes at least two camera arrays.

20. A method for synthesizing a higher resolution image from a plurality of images captured from different viewpoints, comprising:

capturing a plurality of images, where;

the plurality of images are captured using a plurality of Bayer cameras that form at least three rows of cameras and at least three columns of cameras;

the plurality of images include different occlusion sets, wherein the occlusion set of a specific image captured by a given camera is the portion of a scene that is visible to a baseline camera from the plurality of cameras that is occluded from the view of the given camera; and

the plurality of images includes a first image that captures pixels around an edge of a foreground object that is visible to the baseline camera and is in the occlusion set of a second image captured by a second of the plurality of cameras.

21. The method of claim 20, further comprising:

normalizing a set of images using calibration data stored in a storage device using an address conversion module;

detecting and metering parallax using a parallax confirmation and measurement module, where detecting and metering parallax comprises ignoring pixels in the images that are in an exposed occlusion set;

aligning portions of images captured by different cameras to compensate for parallax using an image pixel correlation module based upon the detected and metered parallax and the stored calibration data; and

obtaining a higher resolution image having a resolution that is higher than the resolutions of the images in the set of images using a super-resolution module, where color information around the edge of the foreground object that is visible in the baseline image and in the occlusion set of the second image is reconstructed in the higher resolution image using the pixels captured by the first image.