Raw sensor image and video de-hazing and atmospheric light analysis methods and systems

1. A method for processing image or video data performed in an image processing pipeline, the method comprising:

receiving color filtered mosaiced raw image or video data, de-hazing the color filtered mosaiced raw image or video data to create de-hazed mosaiced image or video data and

de-mosaicing the de-hazed mosaiced image or video data to create de-hazed and de-mosaiced image or video data, wherein the de-hazing comprises de-hazing a single data set of a single raw image,

wherein the de-hazing comprises estimating atmospheric light in a subsampled version of the single raw image, and wherein said estimating applies a first assumption that atmospheric light varies smoothly in local neighborhood regions and the pixel values are similar to each other in the local neighborhood regions, and applies a second assumption that edges and details need not be preserved while estimating atmospheric light.

2. The method of claim 1 , further comprising generating a full color image or video from the de-hazed and de-mosaiced image or video data.

3. The method of claim 1 , wherein the de-hazing treats the color filtered mosaic data as piecewise constant and replaces missing pixels in the color filtered mosaic data with nearest neighbor pixels.

4. The method of claim 3 , wherein the de-hazing comprises a kernel based de-hazing method.

5. The method of claim 3 , wherein the de-hazing applies a dark channel prior method to create the de-hazed mosaiced image or video data.

6. The method of claim 5 , comprising the dark channel prior method using one color channel and finding substitute values for other color channels.

7. The method of claim 3 , wherein the de-hazing comprises a pixel based de-hazing method.

8. The method of claim 3 , wherein the de-hazing comprises an adaptive Wiener filter de-hazing method.

9. The method of claim 8 , wherein minimum channels in the color filtered mosaiced raw image or video data are measured using adjacent pixels for a local region of pixels.

10. The method of claim 1 , wherein the color filtered mosaiced raw image or video data comprises Bayer image data.

11. A camera including an image sensor and a color filter and an image processing pipeline, the image processing pipeline being configured to perform de-hazing of color filtered mosaiced raw image or video data according to claim 1 .

12. The method of claim 1 , wherein the image processing pipeline comprises a pipeline implemented in a machine vision system.

13. The method of claim 1 , wherein the de-hazing treats atmospheric light as invariant in an entirety of the single raw image.

14. The method of claim 1 , wherein the de-hazing and de-mosaicing are conducted on the single data set of the single raw image and then conducted on single data sets of additional single raw images.

15. The method of claim 1 , wherein the de-hazing comprises a patch-based de-hazing algorithm.

16. The method of claim 1 , wherein each single raw image in a series of raw images is directly recovered via the de-hazing and the de-mosaicing.

17. A method for processing image or video data performed in an image processing pipeline, the method comprising:

receiving color filtered mosaiced raw image or video data, de-hazing the color filtered mosaiced raw image or video data to create de-hazed mosaiced image or video data and de-mosaicing the de-hazed mosaiced image or video data to create de-hazed and de-mosaiced image or video data, wherein the de-hazing comprises de-hazing a single data set of a single raw image, and

wherein the de-hazing comprises estimating haze in a local neighborhood region of the single raw image and de-hazing the entire single raw image from estimated haze in the local neighborhood region.

18. A camera including an image sensor and a color filter and an image processing pipeline, the image processing pipeline being configured to perform de-hazing of color filtered mosaiced raw image or video data according to claim 17 .

19. The method of claim 17 , wherein the image processing pipeline comprises a pipeline implemented in a machine vision system.

20. A method for processing image or video data performed in an image processing pipeline, the method comprising:

receiving color filtered mosaiced raw image or video data, de-hazing the color filtered mosaiced raw image or video data to create de-hazed mosaiced image or video data and

de-mosaicing the de-hazed mosaiced image or video data to create de-hazed and de-mosaiced image or video data, wherein the de-hazing comprises de-hazing a single data set of a single raw image,

wherein the de-hazing treats the color filtered mosaic data as piecewise constant and replaces missing pixels in the color filtered mosaic data with nearest neighbor pixels, and

wherein:

the de-hazing defines a new color channel region as a 2×2 block (connected 4-pixel to upper left location) of the raw image so that each of a R, G and B color value can be measured in the raw image;

measures dark channels d p B the raw image within the same spatial region Ω p B of the raw image

d

p

B

=

min

p

∈

Ω

p

B

⁢

x

p

B

x

p

B

=

∑

c

∈

{

r

,

g

,

b

}

⁢

x

p

s

⁡

(

c

)

where x p S is the raw image sampled by the sensor according to a pattern of the color filter;

determines transmission t d B in the raw image as

t

d

B

=

1

-

γ

⁢

min

p

∈

Ω

p

B

⁢

y

p

B

a

B

where y p B is divided by the corresponding atmospheric light color a B measured in pattern of the color filter; and

estimates the c-th color of atmospheric light individually estimated from either of the most haze-opaque regions using bright channels or dark channels.

21. A camera including an image sensor and a color filter and an image processing pipeline, the image processing pipeline being configured to perform de-hazing of color filtered mosaiced raw image or video data according to claim 20 .

22. The method of claim 20 , wherein the image processing pipeline comprises a pipeline implemented in a machine vision system.