1. Color2Gray: Salience-Preserving Color Removal Amy Gooch Sven Olsen Jack Tumblin Bruce Gooch Northwestern University

2. Color Grayscale New Algorithm

3. Color Space Volume of displayable CIE L*a*b* Colors

4. Isoluminant Colors ColorGrayscale

5. Converting to Grayscale… In Color Space – Linear – Nonlinear In Image Space – Pixels (RGB) Using colors in the image Different gray for different color – Relative difference Using colors in the image and their position in image space Colors can map to same gray…..

6. CIE CAM 97Photoshop LAB CIE XYZYCrCb Traditional Methods: Luminance Channels Problem can not be solved by simply switching to a different space

7. Simple Linear Mapping Luminance Axis

8. Principal Component Analysis (PCA) Luminance Axis

9. Contemporaneous Research Rasche et al. [2005, IEEE CG&A and EG] Color Image Luminance Only Rasche et al.'s Method

10. Goals Dimensionality Reduction – From tristimulus values to single channel Loss of information Maintain salient features in color image – Human perception

11. Challenge 1: Influence of neighboring pixels

12. Challenge 2: Dimension and Size Reduction -120, -120 120, 120 0 100

13. Original Challenge 3: Many Color2Gray Solutions......

14. Algorithm Intuition color2gray 12 L1L1 L2L2 i = 1, j = 2 luminance Look at  C L 1 +   L2L2 L 2 +  2,1 L1L1 L1L1 L2L2 L1L1 L2L2 Look at  C

15. Algorithm Overview Adjust g to incorporate both luminance and chrominance differences  ij For every pixel – Compute Luminance distance – Compute Chrominance distance Initialize image, g, with L channel Convert to Perceptually Uniform Space – CIE L*a*b*

16. Color2Grey Algorithm Optimization: min      (g i - g j ) -  i,j   i j=i-  i+ 

17. Parameters Map chromatic difference to increases or decreases in luminance values  Max chrominance offset  Radius of neighboring pixels 

18.  = 2  = 16  = entire image  = 300 o  = 10  = 49 o  = 10  : Neighborhood Size

19.  = 16  = entire image

20.  : Chromatic variation maps to luminance variation  = 5  = 10  = 25   crunch(x) =  * tanh(x/  )

21. Luminance Distance: Problem: ||  C ij || is unsigned  L ij = L i - L j Perceptual Distance Chrominance Distance: ||  C ij ||

22. C2C2 C1C1 Map chromatic difference to increases or decreases in luminance values Color Space +b* +a*-a*

23.  C 1,2  vv sign ( ||  C i,j || ) = sign (  C i,j. v  ) Color Difference Space v  = (cos , sin  ) +  b* +  a*-  a* - - + + -  b*

24. Photoshop Grayscale  = 225  = 45

25. Grayscale  = 45  = 135  = 0

26. How to Combine Chrominance and Luminance  ij  (Luminance)  L ij

27. How to Combine Chrominance and Luminance  ij   L ij ||  C ij || (Luminance) if |  L ij | > ||  C ij || (Chrominance)

28. How to Combine Chrominance and Luminance  ij   L ij crunch(||  C ij ||) if |  L ij | > crunch(||  C ij ||)   crunch(x) =  * tanh(x/  )

29. ...... How to Combine Chrominance and Luminance  ij   L ij crunch(||  C ij ||) if  C ij.  ≥ 0 if |  L ij | > crunch(||  C ij ||) crunch(-||  C ij ||) otherwise Grayscale

30. Color2Grey Algorithm Optimization: min      (g i - g j ) -  i,j   j=i-  If  ij ==  L then ideal image is g Otherwise, selectively modulated by  C ij i i+ 

31. OriginalColor2Gray Photoshop Gray Results Color2Gray + Color

32. OriginalPhotoshopGrayColor2Gray Color2Gray+Color

33. OriginalPhotoshop GrayColor2Gray

34. OriginalPhotoshopGreyColor2Grey

35. Implementation Performance Image of size S x S – O(  2 S 2 ) or O(S 4 ) for full neighborhood case 12.7s 100x100 image 65.6s 150x150 image 204.0s 200x200 image – GPU implementation O(S 2 ) ideal, really O(S 3 ) – 2.8s 100x100 – 9.7s 150x150 – 25.7s 200x200 Athlon 64 3200 CPU NVIDIA GeForce GT6800

36. Future Work Animations/Video Faster – Multiscale Smarter – Remove need to specify  – Image complexity measures

37. Validate "Salience Preserving" OriginalPhotoshopGreyColor2Grey

38. Validate "Salience Preserving" OriginalPhotoshopGrayColor2Gray

39. Thank you SIGGRAPH Reviewers NSF Helen and Robert J. Piros Fellowship Northwestern Graphics Group MidGraph2004 Participants – especially Feng Liu (sorry I spelled your name wrong in the acknowledgements) www.color2gray.info

40. OriginalColor2GrayColor2Gray+Color

41. OriginalColor2GrayColor2Gray+Color

42. Original Color2Gray Color2Gray+Color

43. OriginalPhotoshop GrayColor2Gray

44. OriginalColor2GrayColor2Gray+Color

45. OriginalPhotoshop GrayColor2Gray

46. OriginalColor2GrayColor2Gray+Color

47. Photoshop Grayscale

49. Rasche et al.

50. Photoshop Grayscale Rasche et al.

51. Photoshop Grayscale Rasche et al.

52. Parameter   = 5  = 15  = 25  = 35  = 45  = 55  = 65  = 75  = 85  = 95