Издательство John Wiley, 2007, -408 pp.A human observer is able to recognize the color of objects irrespective of the light used to illuminate the objects. This ability is called color constancy. In photography, color constancy is known under the name white balance. Most amateur photographers have probably experienced the following problem at one time or another when a photograph is taken. Light from a light source is reflected from the objects. The sensors measure the reflected light. The measurements depend on the type of light source used. For instance, if yellow light falls on a white wall, the sensor measures the yellow light that is reflected from the wall. Thus, the resulting colors may not be the same as the colors that were perceived by the observer. The wall will nevertheless appear to be white to a human observer. Digital cameras use postprocessing to achieve an approximately color constant or white-balanced image. Obtaining a color constant descriptor from the image pixels is not only important for digital photography but is also very important for computer vision. Many algorithms work only under one set of lighting conditions but not under another. For instance, an algorithm may work very well under natural lighting but the same algorithm may not work as well when used under artificial illumination. Color constant descriptors are also very important for color-based object recognition. At present, it is not known how color constant descriptors are computed by the human visual system. However, a number of algorithms have been proposed to address the problem of color constancy. The book describes all of the major color constancy algorithms that are known from the literature together with recent research done by the author. Human color perception is only approximately constant as you probably have noticed when buying clothes in a store. If you select a set of seemingly black trousers you may very well find out at home that the selected set of trousers is actually kind of bluish. Color perception is also influenced by the colors which are present in the surround of an object. In this case, color perception could have been influenced by the lack of a sufficiently complex surround. You can find out the color of a set of trousers by putting the trousers next to another set of trousers. If you place a seemingly black set of trousers next to another one you may find out that one is actually kind of dark bluish whereas the other one is indeed black. If you take the black trousers and place them next to black velvet you will think that the trousers are kind of dark grey and that the velvet is actually black. Why color perception sometimes behaves as just described will become clearer after reading this book. This book is intended as a general introduction into the field of color constancy. It may be used as a textbook by students at the graduate level. It is assumed that you have at least some background knowledge in image processing or computer vision, and that you have read at least one introductory textbook to image processing or a general computer vision textbook. The book is intended to be read from front-to-back. Readers with advanced knowledge in the field may of course skip directly to the chapters of interest. Chapters 3, 4, 5, 6 and 7 could be used as an introductory course to computational color constancy. The book is addressed to professionals working with images in computer science where images are processed solely in software. Students as well as professionals in electrical engineering may consult this book when implementing color constancy algorithms into scanners, digital cameras, or display devices. Researchers studying the human visual system may also find it helpful in understanding how image processing is done in a technical field. Given the algorithmic solutions that are presented in this book, it may be possible to arrive at a better understanding on how the human visual system actually processes the available data. When reading the chapter on the human visual system, you should keep in mind that I do not have a medical or biological background. My background is in computer science. Since the field of color constancy is deeply intertwined with human color perception, I have tried my best to give you an accurate as well as an extensive overview about how the human visual system works. Thus, bear with me when I sometimes take a very algorithmic view of human image processing.Introduction The Visual System Theory of Color Image Formation Color Reproduction Color Spaces Algorithms for Color Constancy under Uniform Illumination Algorithms for Color Constancy under Nonuniform Illumination Learning Color Constancy Shadow Removal and Brightening Estimating the Illuminant Locally Using Local Space Average Color for Color Constancy Computing Anisotropic Local Space Average Color Evaluation of Algorithms Agreement with Data from Experimental Psychology Conclusion
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