A method of generating a depth map from a plurality of images captured from different viewpoints, comprising:nnormalizing a set of images using calibration data stored in a storage device using an address conversion module, where:nthe set of images comprises a plurality of images that are:ncaptured from different viewpoints;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; andthe set of images includes:nimages captured using the same imaging characteristics; andimages captured using different imaging characteristics;detecting and metering parallax using a parallax confirmation and measurement module, where detecting and metering parallax comprises:ndetermining the parallax that yields the highest correlation between pixels from images captured using the same imaging characteristics accounting for the positions of the imagers that captured the images by:nperforming redundant pair-wise measurements between pixels from images captured using the same imaging characteristics to determine pixel correlation for different parallax-induced shifts;keeping track of various pair-wise measurements and calculating a parallax difference that yields the highest pixel correlation ignoring pixels in the images that are in an exposed occlusion set; andgenerating a depth map using the parallax confirmation and measurement module based upon the measured parallax.
›2.↳ 1The method of claim 1, wherein:nthe calibration data indicates mappings between addresses of physical pixels in imagers and logical addresses within a…d2
The method of claim 1, wherein:nthe calibration data indicates mappings between addresses of physical pixels in imagers and logical addresses within an image; andthe address conversion module resolves phase differences between the set of images by converting addresses of physical pixels in imagers to logical addresses.
›3.↳ 1The method of claim 1, wherein calculating a parallax difference that yields the highest pixel correlation comprises determining parallax based upon t…d2
The method of claim 1, wherein calculating a parallax difference that yields the highest pixel correlation comprises determining parallax based upon the set of pair-wise measurements that have the best least squares fit.
›4.↳ 1The method of claim 1, wherein aligning portions of images captured by different imagers to compensate for parallax using an image pixel correlation m…d2
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.
›5.↳ 1The method of claim 1, further comprising:naligning portions of different images to compensate for parallax using an image pixel correlation module ba…d2+4
The method of claim 1, further comprising:naligning portions of different images to compensate for parallax using an image pixel correlation module based upon the measured parallax and the stored calibration data; andobtaining 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.
›6.↳ 5The method of claim 5, wherein obtaining a higher resolution image having a resolution that is higher than the resolutions of the images in the set of…d3+1
The method of claim 5, 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.
›7.↳ 6The method of claim 6, wherein obtaining a higher resolution image having a resolution that is higher than the resolutions of the images comprises per…d4
The method of claim 6, 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.
›8.↳ 5The method of claim 5, wherein obtaining a higher resolution image having a resolution that is higher than the resolutions of the images in the set of…d3
The method of claim 5, 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 super-resolution processing on the aligned image portions to synthesize a super-resolution image.
›9.↳ 5The method of claim 5, further comprising selecting at least one distance as a focal plane and applying blurring to pixels in the higher resolution im…d3
The method of claim 5, 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.
›10.↳ 1The method of claim 1, further comprising estimating distance to an object visible in the set of images using the parallax confirmation and measuremen…d2
The method of claim 1, further comprising estimating distance to an object visible in the set of images using the parallax confirmation and measurement module.
›11.↳ 1The method of claim 1, further comprising measuring the absolute size and shape of a physical item visible in the set of images using the parallax con…d2
The method of claim 1, further comprising measuring the absolute size and shape of a physical item visible in the set of images using the parallax confirmation and measurement module.
›12.↳ 1The method of claim 1, wherein the set of images is captured by an array of between 2×2 and 6×6 imagers.d2
The method of claim 1, wherein the set of images is captured by an array of between 2×2 and 6×6 imagers.
›13.↳ 1The method of claim 1, wherein the set of images is captured by a set of imagers that form at least a 3×3 configuration of imagers comprising:nan ima…d2
The method of claim 1, wherein the set of images is captured by a set of imagers that form at least a 3×3 configuration of imagers comprising:nan imager having a green filter at the center of a 3×3 configuration of imagers;two imagers having red filters located on opposite sides of the 3×3 configuration of imagers;two imagers having blue filters located on opposite sides of the 3×3 configuration of imagers; andfour imagers having green filters surrounding the central imager having a green filter.
›14.↳ 1The method of claim 1, wherein the set of images is captured by a linear array of imagers.d2
The method of claim 1, wherein the set of images is captured by a linear array of imagers.
›15.↳ 1The method of claim 1, wherein the linear array of imagers is selected from the group consisting of: a 1×4 array of imagers; and a 1×10 array of ima…d2
The method of claim 1, wherein the linear array of imagers is selected from the group consisting of: a 1×4 array of imagers; and a 1×10 array of imagers.
›16.↳ 1The method of claim 1, wherein each image in the set of images is obtained by an imager including a filter selected from the group consisting of a Bay…d2
The method of claim 1, wherein each image in the set of images is obtained by an imager including a 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.
›17.↳ 1The method of claim 1, wherein at least one of the images in the set of images is captured by an imager selected from the group consisting of: a polyc…d2
The method of claim 1, wherein at least one of the images in the set of images is captured by an imager selected from the group consisting of: a polychromatic imager; and a near-IR imager.
›18.↳ 1The method of claim 1, wherein imagers in the array of imagers have the same resolution.d2
The method of claim 1, wherein imagers in the array of imagers have the same resolution.
›19.↳ 1The method of claim 1, wherein the images in the set of images have different resolutions.d2
The method of claim 1, wherein the images in the set of images have different resolutions.
