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.

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Presentation transcript:

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.

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

13- 3 ○ The Human Eye

13- 4 Two kinds of photoreceptors: rods, cones

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

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

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

13- 8 。 The relationship between RGB and XYZ

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.

。 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

。 RGB Gamut – The colors correspond to positive matching values

。 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

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

○ (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)

。 Example: (R, G, B) = (0.2, 0.4, 0.6)

(ii) HSV RGB

。 Example: (H, S, V) = (0.5833, , 0.6)

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

○ 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

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

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

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

◎ Color Images

13- 24

◎ Pseucoloring 。 Intensity Slicing

。 Transformation Define colormap functions:

◎ Processing of Color Images Two methods: (a) (b)

○ Noise Reduction R G B Apply median filter to R,G,B Apply median filter to Y

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

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

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

13- 32