Algebraic combinatorics by Christopher D. Godsil

By Christopher D. Godsil

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Data sets investigated by CIE TC 1-52 CAT include: Mori et al. [16] from the Color Science Association of Japan, McCann et al. [17] and Breneman [18] using a haploscopic matching technique; Helson et al. [19], Lam and Rigg [20] and Braun and Fairchild [21] using the memory matching technique; and Luo et al. [22, 23] and Kuo and Luo [24] using the magnitude estimation method. These data sets, however, do not include visual saturation correlates. Hence, Juan and Luo [25, 26] investigated a data set of saturation correlates using the magnitude estimation method.

The BFD transform was originally derived by fitting only one data set, Lam and Rigg. Although it gave a reasonably good fit to many other data sets, it predicted badly the McCann data set. In addition, the BFD and CMCCAT97 include an exponent p for calculating the blue corresponding spectral response. This causes uncertainty in reversibility and complexity in the reverse mode. Li et al. [31] addressed this problem and provided a solution by including an iterative approximation using the Newton method.

In fact, Kuo et al. [55] suggested changing each element in the first row slightly. 4 The Brightness Function The brightness function of CIECAM02 is different from the brightness function of the older CIECAM97s model. The major reason for the change [56] was because of the correction to the saturation function (s). However, it has been reported that the brightness prediction of CIECAM02 does not correlate well with the appropriate visual data [57]. More visual brightness data is needed to clarify the brightness function.

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