Image color matching and equalization devices and related methods

1. A method comprising:

using at least one processor for:

determining overlapping portions of a scene within first and second images of the scene;

generating an array of color channel differences between the overlapping portions;

applying a quantization technique to an array of color channel differences for creating a sparse difference color matrix;

identifying empty locations of the sparse matrix and computing interpolated difference color values to fill them; and

modifying the color of at least one pixel of one of the images by performing an inverse look-up in the sparse table utilizing its color, identifying the color difference on the corresponding entry, and applying the color difference on a target pixel.

2. The method of claim 1 , wherein determining overlapping portions of the scene comprises applying an adaptive low-pass filter.

3. The method of claim 1 , wherein determining overlapping portions of the scene comprises determining one of image corners, and image feature points in each of the first and second images.

4. The method of claim 1 , further comprising one of rectifying, and registering the first and second images.

5. The method of claim 1 , further comprising selecting a set of points.

6. The method of claim 5 , further comprising selecting a random set of points.

7. The method of claim 5 , further comprising creating a sparse matrix utilizing a selected set of points and their corresponding color values in both the first and second images.

8. The method of claim 7 , further comprising filtering entries on the sparse matrix that contain more than one color sets and replacing the entry with the filtered value.

9. The method of claim 7 , further comprising filling the empty entries of the sparse matrix by calculating interpolated values of color values found in other parts of the sparse matrix.

10. The method of claim 9 , further comprising performing a curve fitting operation to filter the values of the sparse matrix.

11. The method of claim 10 , further comprising filtering the values of the sparse table by use of a technique that accounts for one of a locality of pixel groupings, and a similarity of colors, and edge boundaries.

12. The method of claim 11 , further comprising:

performing a segmentation operation on the image; and

using the segmented labels as guidance for filtering the localization requirement.

13. The method of claim 1 , further comprising performing a look-up table operation, for each pixel to be corrected, to identify its corresponding entry value on a table.

14. The method of claim 13 , further comprising modifying each pixel to be corrected by use of its corresponding entry value.

15. The method of claim 7 , wherein generating the array of color channel differences comprises:

determining R, G, and B values of the overlapping portions of the reference image;

determining R, G, and B values of the overlapping portions of the image to be corrected; and

using the R, G, and B values to generate the array of color channel differences.

16. The method of claim 1 , further comprising generating a look-up table for correction, wherein the look-up table comprises color difference values between the first and second images.

17. The method of claim 1 , further comprising generating one of a panoramic image set and a three-dimensional image set using an equalized image.

18. The method of claim 1 , further comprising capturing the first and second images of the scene.