Simple and robust color saturation adjustment for digital images
A method and system for adjusting saturation in digital images that operates as closely as possible to the long-, medium-, short-(LMS) cone spectral response space. According to the method, a sensor component image such as an RGB image from a digital imager is input and converted to the LMS space. White point adaptation and equalization are performed on the LMS data. The saturation adjustment is then performed by applying a stretching transformation to the L and S LMS components with respect to the M component of each pixel.
1. A method for adjusting color saturation of a digital color image comprising:
transforming the image to an LMS color space having a plurality of long-, medium-, and short-wavelength (LMS) components;
calculating white point adaptation levels for each of the plurality of LMS components;
adjusting each of the plurality of LMS components based on the associated white point adaptation levels;
adjusting the saturation of the LMS space by performing a transformation of said L components and said S components; and
applying said transformed L components and S components to said LMS color space.
2. The method if claim 1 , wherein the color image is input from an image sensor.
3. The method of claims 1 , wherein the color image is input from a digital image sensor.
4. The method of claim 1 , wherein the color image is input from a CMOS image sensor.
5. The method of claim 1 , wherein the color image is an RGB image.
6. The method of claim 1 , wherein said step of adjusting the saturation of the LMS space comprises the step of transforming said L components and said S components with respect to said M component.
7. The method of claim 6 , wherein said step of transforming said L components and said S components with respect to said M component comprises identifying and applying a saturation adjustment factor K to said L components, said S components, and said M component.
8. The method of claim 7 , wherein each L component is transformed according to the equation
L 1 =M+K ( L 0 −M ),
where M is a Medium component, L 0 is an initial Long component, and L 1 is a transformed Long component.
9. The method of claim 7 , wherein each S component is transformed according to the equation
S 1 =M+K ( S 0 −M ),
where M is a Medium component, S 0 is an initial Short component, and S 1 is a transformed Short component.
10. The method of claim 1 further comprising the step of transforming said LMS color space image to an output image.
11. An imager comprising:
means for transforming the image to an LMS color space having a plurality of long-, medium-, and short-wavelength (LMS) components;
means for calculating white point adaptation levels for each of the plurality of LMS components;
means for adjusting each of the plurality of LMS components based on the associated white point adaptation levels;
means for adjusting the saturation of the LMS space by performing a transformation of said L components and said S components; and
means for applying said transformed L components and S components to said LMS color space.
12. The imager of claim 11 , wherein said means for transforming, calculating, adjusting, and applying comprises one of hardware, software, and a combination of hardware and software.
13. The imager of claim 11 , wherein said means for transforming, calculating, adjusting, and applying comprises an image processor.
14. An imaging device comprising:
a transforming unit for transforming the image to an LMS color space having a plurality of long-, medium-, and short-wavelength (LMS) components;
a calculating unit for calculating white point adaptation levels for each of the plurality of LMS components;
an adjusting unit for adjusting each of the plurality of LMS components based on the associated white point adaptation levels;
a second adjusting unit for adjusting the saturation of the LMS space by performing a transformation of said L components and said S components; and
an applying unit for applying said transformed L components and S components to said LMS color space.
15. The imaging device of claim 14 , further comprising a display device having a screen, and circuitry for displaying an RGB component image on said screen.
16. The imaging device of claim 14 , wherein the color image is input from an image sensor.
17. The imaging device of claim 14 , wherein the color image is input from a digital image sensor.
18. The imaging device of claim 14 , wherein the color image is input from a CMOS image sensor.
19. The imaging device of claim 14 , wherein the color image is an RGB image.
20. The imaging device of claim 14 , wherein said step of adjusting the saturation of the LMS space comprises the step of transforming said L components and said S components with respect to said M component.
21. The imaging device of claim 20 , wherein said step of transforming said L components and said S components with respect to said M component comprises identifying and applying a saturation adjustment factor K to said L components, said S components, and said M component.
22. The imaging device of claim 21 , wherein each L components is transformed according to the equation
L 1 =M+K ( L 0 −M ),
where M is a Medium component, L 0 is an initial Long component, and L 1 is a transformed Long component.
23. The imaging device of claim 21 , wherein each S component is transformed according to the equation
S 1 =M+K ( S 0 −M ),
where M is a Medium component, S 0 is an initial Short component, and S 1 is a transformed Short component.
24. A storage medium containing a program for adjusting the color saturation of a digital color image, the program comprising instructions for transforming the image to an LMS color space having a plurality of long-, medium-, and short-wavelength (LMS) components; calculating white point adaptation levels for each of the plurality of LMS components; adjusting each of the plurality of LMS components based on the associated white point adaptation levels; adjusting the saturation of the LMS space by performing a transformation of said L components and said S components; and applying said transformed L components and S components to said LMS color space.
25. The storage medium of claim 24 , wherein the color image is input from an image sensor.
26. The storage medium of claim 24 , wherein the color image is input from a digital image sensor.
27. The storage medium of claim 24 , wherein the color image is input from a CMOS image sensor.
28. The storage medium of claim 24 , wherein the color image is an RGB image.
29. The storage medium of claim 24 , wherein said step of adjusting the saturation of the LMS space comprises the step of transforming both said L components and said S components with respect to said M component.
30. The storage medium of claim 29 , wherein said step of transforming both said L components and said S components with respect to said M component comprises identifying and applying a saturation adjustment factor K to said L components, said S components, and said M component.
31. The storage medium of claim 30 , wherein each L component is transformed according to the equation
L 1 =M+K ( L 0 −M ),
where M is a Medium component, L 0 is an initial Long component, and L 1 is a transformed Long component.
32. The storage medium of claim 30 , wherein each S component is transformed according to the equation
S 1 =M+K ( S 0 −M ),
where M is a Medium component, S 0 is an initial Short component, and S 1 is a transformed Short component.
33. A method for adjusting the saturation of an LMS component image having a plurality of long-, medium-, and short wavelength components comprising using a processor for stretching said Long components and said Short components with respect to said Medium component.
34. The method of claim 33 , wherein said stretching said Long components and said Short components with respect to said Medium component comprises identifying and applying a saturation adjustment factor K to said Long components, said Short components, and said Medium component.
35. The method of claim 34 , wherein each Long component is stretched according to the equation
L 1 =M+K ( L 0 −M ),
where M is a medium component, L 0 is an initial Long component, and L 1 is a transformed Long component.
36. The method of claim 34 , wherein each Short component is stretched according to the equation
S 1 =M+K ( S 0 −M ),
where M is a medium component, S 0 is an initial Short component, and S 1 is a transformed Short component.
37. An imager comprising a processor for adjusting the saturation of an LMS component image having a plurality of long-, medium-, and short-wavelength components to stretch said Long components and said Short components with respect to said Medium component.
38. The imager of claim 37 , wherein said of stretching said Long components and said Short components with respect to said Medium component comprises identifying and applying a saturation adjustment factor K to said Long components, said Short components, and said Medium component.
39. The imager of claim 38 , wherein each Long component is stretched according to the equation
L 1 =M+K ( L 0 −M ),
where M is a medium component, L 0 is an initial Long component, and L 1 is a transformed Long component.
40. The imager of claim 38 , wherein each Short component is stretched according to the equation
S 1 =M+K ( S 0 −M ),
where M is a medium component, S 0 is an initial Short component, and S 1 is a transformed Short component.