1. 13- 1 Chapter 13: Color Processing 。 Color: An important descriptor of the world 。 The world is itself colorless 。 Color is caused by the vision system responding differently to different wavelengths of light.

2. 13- 2 。 Image color depends on: (1) The color of the incidence light (2) The color of the scene surface (3) The nature of the visual sensor

3. 13- 3 ○ The Human Eye

4. 13- 4 Two kinds of photoreceptors: rods, cones

5. 13- 5 Rods -- sensitive to light Cones -- sensitive to color Three types of cones:

6. 13- 6 ○ RGB Color Space -- Many colors are made up of varying amounts of red, green and blue R, G, B: primary colors, real : color matching functions may be negative

7. 13- 7 ○ CIE XYZ Color Space CIE (Commission Internationale d’Eclairage): an organization responsible for color standard X,Y,Z: not real primaries, Y: luminance Their color matching functions are positive everywhere 。 The volume of visible colors in CIE XYZ space is a cone

8. 13- 8 。 The relationship between RGB and XYZ

9. 13- 9 ○ CIE xy Color Space -- A constant brightness section intersects the XYZ space with the plane Since x + y + z = 1, a color can be specified by x and y alone.

10. 13- 10 。 Chromaticity Diagram (i) Spectral locus: the curved boundary along which colors of single wavelengths are viewed (ii) Neutral point: the color whose weights are equal for all three primaries (iii) Colors that lie farther away from the neutral point are more saturated

11. 13- 11 。 RGB Gamut – The colors correspond to positive matching values

12. 13- 12 。 Secondary colors (primaries of pigments): Magenta (purple) = R + B = W - G Cyan = G + B = W - R Yellow = R + G = W - B 。 Pigments remove color from incident light, which is reflected from paper e.g., Red ink absorbs green and blue light; incident red light passes through the ink and is reflected from the paper

13. 13- 13 ○ HSV (Hue, Saturation, Value) Color Space Hue: varies from red  green Saturation: varies from red  pink Brightness: varies from black  white

14. 13- 14 ○ (i) RGB HSV If R = V, then If G = V, then If B = V, then If H ends up being negative, add 1 If (R,G,B) = (0,0,0), then (H,S,V) = (0,0,0)

15. 13- 15 。 Example: (R, G, B) = (0.2, 0.4, 0.6)

16. 13- 16 (ii) HSV RGB

17. 13- 17 。 Example: (H, S, V) = (0.5833, 0.6667, 0.6)

18. 13- 18 ○ YIQ Color Space – Used for TV and video Y : luminance information I, Q : color information

19. 13- 19 ○ Uniform Color Space -- The distance in the space is a guide to color difference 。 Noticeable difference – the difference when modifying a color until one can tell it has changed 。 Macadam ellipse -- the noticeable difference of a color forms the boundary of the color in a color space and can be fitted with an ellipse

20. 13- 20 The color difference in CIE xy space is poor: (a) the ellipses at the top are larger than those at the bottom (b) the ellipses rotate as they move up

21. 13- 21 。 CIE u’v’ Color Space – a more uniform space than the CIE xy color space

22. 13- 22 ○ CIE Lab Color Space – another substantial uniform space where : the XYZ coordinates of a reference white patch

23. 13- 23 ◎ Color Images

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25. 13- 25 ◎ Pseucoloring 。 Intensity Slicing

26. 13- 26 。 Transformation Define colormap functions:

27. 13- 27 ◎ Processing of Color Images Two methods: (a) (b)

28. 13- 28 ○ Noise Reduction R G B Apply median filter to R,G,B Apply median filter to Y

29. 13- 29 ○ Contrast Enhancement Perform on the intensity component (1) RGB  YIQ (2) Apply histogram equalization to Y  Y’ (3) Y’IQ  R’G’B’

30. 13- 30 ○ Spatial Filtering Both low- and high- pass filters are better off applying to the intensity component

31. 13- 31 ○ Edge Detection Two ways: (1) Apply edge detection to the intensity component (2) Apply edge detection to each RGB component

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