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Normalized space average color

Figure 6.28 Results of comprehensive color normalization using local space average color instead of global space average color. The intensities of the input image were used to rescale the output pixels. Figure 6.28 Results of comprehensive color normalization using local space average color instead of global space average color. The intensities of the input image were used to rescale the output pixels.
Figure 11.8 The color of the current pixel c, and local space average color a are projected onto the plane r + g + b = 1. Let c and a be the normalized points. Now, normalized local space average color is projected onto the gray vector w. The projection is subtracted from a, which gives us ax- The component ax is orthogonal to the gray vector w. This component is subtracted from the color of the current pixel that gives us the normalized output color 6. Finally, the output color is scaled back to the intensity of the input pixel. Figure 11.8 The color of the current pixel c, and local space average color a are projected onto the plane r + g + b = 1. Let c and a be the normalized points. Now, normalized local space average color is projected onto the gray vector w. The projection is subtracted from a, which gives us ax- The component ax is orthogonal to the gray vector w. This component is subtracted from the color of the current pixel that gives us the normalized output color 6. Finally, the output color is scaled back to the intensity of the input pixel.
Figure 11.10 Computation of color constant descriptors using normalized color shifts. The first layer is the input layer. The second layer computes local space average color. The output is computed in the third layer. The measured red, green, and blue components are stored in cells c, with i e r, g, b. The average of these three components is stored in cell c. Space average color is stored in cells a,, the average of these three components in stored in a. Output cells are denoted by n, (from Ebner 2003c). Figure 11.10 Computation of color constant descriptors using normalized color shifts. The first layer is the input layer. The second layer computes local space average color. The output is computed in the third layer. The measured red, green, and blue components are stored in cells c, with i e r, g, b. The average of these three components is stored in cell c. Space average color is stored in cells a,, the average of these three components in stored in a. Output cells are denoted by n, (from Ebner 2003c).
The algorithm described in Section 11.3 normalizes both the color of the input pixel and local space average color before subtracting local space average color from the color of the input pixel. The resulting color is then scaled to have the same intensity as the input pixel. Let cp be the color of the input pixel and let a be the local space average color. Then, the... [Pg.313]

Comprehensive color normalization based on local space average color was discussed in Section 6.7. As we have already seen earlier, after the first step of the algorithm, when the colors are normalized, the reflectance of either the sample or the background drops out of the equation. After normalization, we obtain the output o ... [Pg.315]

Comprehensive color normalization using local space average color. [Pg.338]

Local space average color, normalized color shifts. [Pg.338]


See other pages where Normalized space average color is mentioned: [Pg.246]    [Pg.246]    [Pg.133]    [Pg.236]    [Pg.237]    [Pg.243]    [Pg.249]    [Pg.290]    [Pg.324]    [Pg.367]    [Pg.281]    [Pg.411]    [Pg.69]   
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