Color ConstancyA human observer is able to recognize the color of objects irrespective of the light used to illuminate them. This is called color constancy. A digital camera uses a sensor to measure the reflected light, meaning that the measured color at each pixel varies according to the color of the illuminant. Therefore, the resulting colors may not be the same as the colors that were perceived by the observer. Obtaining color constant descriptors from image pixels is not only important for digital photography, but also valuable for computer vision, color-based automatic object recognition, and color image processing in general. This book provides a comprehensive introduction to the field of color constancy, describing all the major color constancy algorithms, as well as presenting cutting edge research in the area of color image processing. Beginning with an in-depth look at the human visual system, Ebner goes on to:
Color Constancy is an ideal reference for practising engineers, computer scientists and researchers working in the area of digital color image processing. It may also be useful for biologists or scientists in general who are interested in computational theories of the visual brain and bio-inspired engineering systems. |
Contents
| xiii | |
| 1 | |
| 9 | |
3 Theory of Color Image Formation | 39 |
4 Color Reproduction | 67 |
5 Color Spaces | 87 |
6 Algorithms for Color Constancy under Uniform Illumination | 103 |
7 Algorithms for Color Constancy under Nonuniform Illumination | 143 |
14 Agreement with Data from Experimental Psychology | 303 |
15 Conclusion | 327 |
Appendix A Dirac Delta Function | 329 |
Appendix B Units of Radiometry and Photometry | 331 |
Appendix C Sample Output from Algorithms | 333 |
Appendix D Image Sets | 339 |
Appendix E Program Code | 349 |
Appendix F Parameter Settings | 363 |
8 Learning Color Constancy | 193 |
9 Shadow Removal and Brightening | 213 |
10 Estimating the Illuminant Locally | 219 |
11 Using Local Space Average Color for Color Constancy | 239 |
12 Computing Anisotropic Local Space Average Color | 255 |
13 Evaluation of Algorithms | 275 |
| 369 | |
List of Symbols | 381 |
| 385 | |
Permissions | 391 |
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Common terms and phrases
Anisotropic Anisotropic L.S.A. color Anisotropic local space assume background black-body radiator blue BRDF camera color channel color constancy algorithm color histogram color space components cones constant illumination convex hull coordinate cube curve described in Section div2 Ebner Finlayson function Funt gamma correction gamut ganglion cells gradient gray vector gray world assumption green HSV color space human visual system image pixel image sets input image input pixel intensity intersection intrinsic image irradiance Laplacian lateral geniculate nucleus layer light source line of constant linear local space average located logarithm measured method Mondrian neurons object recognition obtain opponent cells output color output image parameter pixel processing element receptors rectangle reflectance rescaled resistive grid response retina retinex retinex theory RGB color space sample saturation scaling scene sensor shown in Figure shows space average color subtracted threshold transform wavelength white patch retinex yellow