Systems and Methods for Synthesizing High Resolution Images Using a Set of Geometrically Registered Images
US-2015042833-A1 · Feb 12, 2015 · US
US11412158B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11412158-B2 |
| Application number | US-202016907016-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jun 19, 2020 |
| Priority date | May 20, 2008 |
| Publication date | Aug 9, 2022 |
| Grant date | Aug 9, 2022 |
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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.
Opening claim text (preview).
What is claimed is: 1. A method of generating a depth map from a plurality of images captured from different viewpoints, comprising: capturing a plurality of images from different viewpoints, where each image includes pixels that are occluded in at least one other image from the plurality of images; normalizing the plurality of images based upon calibration data; measuring parallax between the normalized images by adaptively comparing the similarity of neighborhoods of pixels for different parallax-induced shifts; and generating a depth map using the measured parallax information. 2. The method of claim 1 , wherein the plurality of images are captured by at least one camera array. 3. The method of claim 1 , wherein the plurality of images are captured by a plurality of cameras. 4. The method of claim 3 , wherein the plurality of images 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. 5. The method of claim 3 , wherein cameras in the plurality of cameras are configured to operate with at least one difference in operating parameters. 6. The method of claim 1 , wherein the plurality of images are low resolution images, wherein the method further comprises generating at least one higher resolution super-resolved image using a plurality of the low resolution images by performing parallax detection to generate parallax information to align portions of the plurality of captured low resolution images. 7. The method of claim 1 , wherein measuring parallax comprises determining the parallax that yields the highest correlation between pixels from the plurality of images. 8. The method of claim 1 , wherein measuring parallax comprises calculating a parallax difference that yields a highest pixel correlation, wherein the parallax difference that yields the highest pixel correlation is determined by keeping track of various pair-wise measurements. 9. The method of claim 1 , further comprising performing pair-wise measurements of neighborhoods of pixels to determine pixel similarity for different parallax-induced shifts. 10. The method of claim 9 , further comprising determining a parallax that yields a highest similarity between pixels from images captured by keeping track of various pair-wise measurements of neighborhoods of pixels and calculating a parallax that yields the highest similarity as the best least squares fit of the pair-wise measurements of neighborhoods of pixels. 11. The method of claim 1 , further comprising generating at least one image by fusing aligned portions of the plurality of captured images using the depth map. 12. The method of claim 11 , further comprising performing super-resolution processing on the fused image portions to synthesize a super-resolution image. 13. The method of claim 1 , further comprising generating a higher resolution super-resolved image synthesized using the plurality of images and the parallax measurements to compensate for parallax in the plurality of images. 14. The method of claim 1 , further comprising identifying occluded pixels based upon the measured parallax information. 15. The method of claim 1 , wherein comparing the similarity of neighborhoods of pixels for different parallax-induced shifts comprises comparing the similarity of neighborhoods of pixels for different parallax-induced shifts along scan lines. 16. The method of claim 1 , 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. 17. The method of claim 1 , wherein the at least one camera array is used in a mobile devices. 18. The method of claim 1 , further comprising sending the processed image is then for display. 19. The method of claim 1 , further comprising aligning portions of the plurality of captured images to compensate for the parallax. 20. The method of claim 1 , further comprising comparing a difference between average values of neighboring pixels with a threshold and flagging a potential presence of parallax when the difference exceeds the threshold.
including elements passing infrared wavelengths · CPC title
based on four or more different wavelength filter elements · CPC title
including elements passing panchromatic light, e.g. filters passing white light · CPC title
Pixels for depth measurement, e.g. RGBZ · CPC title
acquired simultaneously · CPC title
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