SYSTEMS AND METHODS FOR SYNTHESIZING HIGHER RESOLUTION IMAGES USING A SET OF IMAGES CONTAINING A BASELINE IMAGE

• US 20140354853A1
• Filed: 08/13/2014
• Published: 12/04/2014
• Est. Priority Date: 05/20/2008
• Status: Active Grant

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: Pelican Imaging Corporation
• Inventors: Venkataraman, Kartik, Jabbi, Amandeep S., Mullis, Robert H., Duparre, Jacques, Hu, Shane Ching-Feng
• Granted Patent: US 9,055,233 B2
• Time in Patent Office: Days
• US Class Current: 348/239
• 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 25/67 : 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 method of synthesizing a higher resolution image from a plurality of images captured from different viewpoints, comprising:

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

the set of images comprises a plurality of images that are;

captured from different viewpoints and include sampling diversity;

include different occlusions sets;

wherein the occlusion set of a first image is the portion of a scene visible in a second image that is occluded in the first image; and

the set of images includes;

images captured using the same imaging characteristics;

images captured using different imaging characteristics; and

a first image that captures pixels around an edge of a foreground object that is visible in a baseline image and is in the occlusion set of a second image captured using the same imaging characteristics as the first imager;

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 imagers 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.

2. The method of claim 1, wherein:

the calibration data indicates mappings between addresses of physical pixels in imagers and logical addresses within an image; and

the address conversion module resolves phase differences between the set of images by converting addresses of physical pixels in imagers to logical addresses.

3. The method of claim 1, further comprising performing normalization of the color planes of the set of images using an upstream pipeline processing module.

4. The method of claim 1, further comprising performing a process to adjust the set of images using an upstream pipeline processing module, where the process is selected from the group consisting of:

black level calculation and adjustments;

fixed noise compensation;

optical point spread function deconvolution;

noise reduction;

lateral color correction; and

crosstalk reduction.

5. The method of claim 1, further comprising performing temperature normalization using an upstream pipeline processing module based upon a temperature measurement.

6. The method of claim 5, wherein performing temperature normalization comprises performing a refractive index normalization using a stored point spread function selected based upon the temperature measurement.

7. The method of claim 1, wherein detecting and metering parallax comprises determining the parallax that yields the highest correlation between pixels from images captured using same imaging characteristics accounting for the positions of the imagers that captured the images.

8. The method of claim 7, wherein determining the parallax that yields the highest correlation between pixels from images captured using similar integration time conditions comprises performing pair-wise measurements to determine pixel correlation for different parallax-induced shifts.

9. The method of claim 8, wherein determining the parallax that yields the highest correlation between pixels from images captured using similar integration time conditions further comprises keeping track of various pair-wise measurements and calculating a parallax difference that yields the highest correlation as the best least squares fit of the pair-wise measurements.

10. The method of claim 1, wherein aligning portions of images captured by different imagers to compensate for parallax using an image pixel correlation module further comprises determining appropriate X and Y offsets to be applied to logical pixel address calculations using an address conversion module based upon the detected and metered parallax and the stored calibration data.

11. The method of claim 1, wherein obtaining a higher resolution image having a resolution that is higher than the resolutions of the images in the set of images comprises fusing the aligned image portions.

12. The method of claim 11, wherein image fusion is performed by interpolating luminance information from the aligned image portions to each grid point on the higher resolution image.

13. The method of claim 11, wherein obtaining a higher resolution image having a resolution that is higher than the resolutions of the images comprises performing super-resolution processing on the fused image portions to synthesize a super-resolution image.

14. The method of claim 1, wherein obtaining a higher resolution image having a resolution that is higher than the resolutions of the images in the set of images comprises performing a super-resolution processing on the aligned image portions to synthesize a super-resolution image.

15. The method of claim 1, further comprising generating a depth map using the parallax confirmation and measurement module.

16. The method of claim 15, further comprising selecting at least one distance as a focal plane and applying blurring to pixels in the higher resolution image with depths in the depth map that are not proximate a focal plane using the super-resolution processing module.

17. The method of claim 11, wherein:

images in the set of images are captured with different exposure times; and

normalizing a set of images further comprises linearizing the camera response in the images based upon exposure time.

18. The method of claim 1, further comprising:

capturing the set of images using an array of imagers;

wherein each imager includes a spectral filter selected from the group consisting of a Bayer filter, one or more Blue filters, one or more Green filters, one or more Red filters, one or more shifted spectral filters, one or more near-IR filters, and one or more hyper-spectral filters.

19. The method of claim 1, wherein the address conversion module, the parallax confirmation and measurement module, the image pixel correlation module, and the super-resolution module are implemented using a general-purpose computer selectively reconfigured by a computer program stored in the computer.

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

normalizing a set of images using calibration data stored in a storage device using an address conversion module, where the set of images comprises a plurality of images that are;

captured from different viewpoints and include sampling diversity;

include different occlusions sets;

wherein the occlusion set of a first image is the portion of a scene visible in a second image that is occluded in the first image; and

the set of images includes;

images captured using the same imaging characteristics;

images captured using different imaging characteristics;

a first image that captures pixels around an edge of a foreground object that is visible in a baseline image and is in the occlusion set of a second image captured using the same imaging characteristics as the first imager;

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 imagers to compensate for parallax using an image pixel correlation module based upon the detected and metered parallax and the stored calibration data;

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; and

generating a depth map for the higher resolution image using the parallax confirmation and measurement module;

wherein the higher resolution image is obtained by;

fusing the aligned image portions; and

performing super-resolution processing on the fused image portions to synthesize a super-resolution image.