Study On Some Problems Of Color Appearance Model CIECAM02

The 1931 CIE (COMMISSION INTERNATIONALE DE L′èCLAIRAGE) colorimetric system has established a basis for the development of theory and application technology of color science. However, during the eighties of the 20th century, while the information technology represented by computers has obtained rapid progress, the problems of true color information transformation and communication in various color information communication systems could not be resolved by the traditional colorimetric theory, thereout a durative research upsurge of color appearance model (CAM) has been brought in the field of color science.For realizing the high perceptional quality cross-media color reproduction, CAMs are necessary. CIE TC1-34 set up a simplized edition of color appearance model― CIECAM97s in 1997. After lots of tests for four years, CIE published the CIECAM02 in 2002, which is a revised edition of CIECAM97s by adding some supplements and making the latter more practical. But as we have noticed, in the color related industries, no CAM has been adopted by any color management system so far. For instance, ICC (International Color Consortium), which is devoting to cross-media color information communication, has never adopted any CAM in ICC profiles. Therefore, it is considered that the theory and application of traditional CAMs are still at the stage of development and testing.Considering the application complexity of traditional CAMs, we proposed a conception of"medium-dependent CAM", which connects directly the driving parameters of color media with color appearance attributes (including illumination, background, surrounds etc.). The"medium- dependent CAM"can be applied to various close loop control systems of, as well as integrated with the prevalent"ICC profile"of open systems. Accordingly, the whole system gets simplized. Based on the conditions of characteristics of CAMs and the operation speed in practical application, neural networks were adopted to realize this model.Due to the complexity of the traditional CAM in color reproduction applications, we proposed a"visual matching"method to get sample data pairs needed by the training of neural networks, and tested the reliability of experimental data from"visual matching"using CIECAM02. Then these data were generalized by neural networks to establish a neural network based module of"medium-dependent CAM". To improve the generalization capability of neural networks, the arrangement order of training samples were optimized and the color spaces transform was implemented. We put forward and realized some combination assessment methods of various subjective assessments and instrument measurements. At the same time, we also realized CRT characterization using"visual matching"and neural networks. Since this kind of method involves the chromatic adaptation factor of human eyes, it is a color appearance based characterization method under some given viewing conditions. A succinct color reproduction data chain has been constructed, and the reproductions from NCS color chips (hardcopy) to CRT displays (softcopy) have been realized according to this method.In addition, due to the fact that CIECAM02 can only make accurate color appearance prediction for colors under achromatic backgrounds, has have proposed a comparatively simple pre-process method for the input color under chromatic background so that CIECAM02 can make accurate prediction when the data obtained by the pre-processing are taken as inputs. Based on opponent-colors theory, we obtained a color induction formula for pre-processing through psychophysical visual experiments. By comparing the results from with pre-processing and without pre-processing, it is clear that the pre-processing can improve the prediction accuracy, and this means that the proposition of pre-processing should be meaningful and valuable.