Systems and methods for normalizing image data captured by camera arrays

1. A method for normalizing image data captured by camera arrays, comprising:

obtaining calibration data for an imager array by capturing images using the imager array, where the calibration data indicates mappings between addresses of physical pixels in imagers and logical addresses within an image;

storing the calibration data in a storage device;

normalizing a set of images with respect to an image captured by a baseline imager within the imager array based upon the 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;

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

wherein normalizing a set of images with respect to an image captured by a baseline image comprises:

correcting color differences between the images with respect to an image captured by a baseline imager; and

correcting geometric distortion differences between the captured images with respect to an image captured by a baseline imager.

2. The method of claim 1 , wherein normalizing the set of images further comprises:

black level calculation and adjustments;

fixed noise compensation; and

optical point spread function deconvolution.

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

4. The method of claim 3 , wherein performing temperature normalization comprises performing a refractive index normalization using a stored point spread function selected based upon the temperature measurement.

5. The method of claim 1 , wherein correcting color differences between the images further comprises:

obtaining a normalization plane;

fitting a polynomial to the normalization plane by scanning the normalization plane using a space filling curve;

storing fitted polynomials as calibration data; and

correcting color differences between images with respect to an image captured by a baseline imager using the fitted polynomials.

6. The method of claim 5 , wherein obtaining a normalization plane comprises:

capturing images of a scene with flat reflectance and calculating a color ratio surface;

removing the black level offset from the pixel values in the captured images; and

low pass filtering the pixel values in the captured images to reduce noise; and

calculating a normalization plane.

7. The method of claim 6 , wherein:

the imager array comprises Green imagers that include Green spectral filters including a baseline Green imager, Red imagers that include Red spectral filters, and Blue spectral filters;

a normalization plane is obtained for each of the Red and Blue imagers; and

a normalization plane is calculated for at least one of Red imagers by determining:

Norm R=G ( i,j )/( R ( i,j )×( G center /R center ))

where G is the baseline Green imager, R is a Red imager being normalized with respect to the baseline Green imager, (i, j) describe the pixel position, and G center , and R center , are the pixel values at the center position.

8. The method of claim 5 , wherein the space filling curve is a spiral space filling curve.

9. The method of claim 8 , wherein a 6 th order polynomial represented using seven coefficients is fitted to the normalization plane using the space filling curve.

10. The method of claim 5 , further comprising:

determining a sensitivity adjustment factor during calibration; and

applying the inverse of the sensitivity adjustment factor when correcting color differences.

11. The method of claim 1 , further comprising 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.

12. The method of claim 1 , further comprising:

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 to 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.

13. The method of claim 12 , 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.

14. The method of claim 13 , 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.

15. The method of claim 12 , wherein obtaining an image having a resolution that is higher than the resolutions of the images in the set of images comprises performing at least on process selected from the group consisting of:

fusing the aligned image portions;

obtaining an 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.

16. The method of claim 1 , wherein each imager in the array of imagers 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 fillers.

17. The method of claim 16 , wherein the baseline imager includes a Green filter.

18. The method of claim 1 , wherein the imagers in the imager array have different resolutions.

19. A method for normalizing image data captured by camera arrays, comprising:

obtaining calibration data for imagers in an imager array by capturing images using the imager array, where the calibration data indicates mappings between addresses of physical pixels in imagers and logical addresses within an image;

storing the calibration data in a storage device;

normalizing a set of images with respect to an image captured by a baseline imager within the imager array based upon the 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;

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

wherein obtaining calibration data comprises:

obtaining a normalization plane by:

capturing images of scene with flat reflectance and calculating a color ratio surface;

removing the black level offset from the pixel values in the captured images;

low pass filtering the pixel values in the captured images to reduce noise; and

calculating a normalization plane;

fitting a polynomial to the normalization plane by scanning the normalization plane using a space filling curve; and

storing fitted polynomials as calibration data in the storage device; and

wherein normalizing a set of images with respect to an image captured by a baseline image comprises:

correcting color differences between images with respect to an image captured by a baseline imager using the fitted polynomials: and

correcting geometric distortion differences between the captured images with respect to an image captured by a baseline imager.