“…The CMCCAT2000 formula removes this problem by simplifying its structure. Sobagaki et al (1999) showed that the CMCCAT97 gives large errors for predicting corresponding colours under the very dim saturated yellow illumination used in one of the McCann experimental phases. Later, a new model, the CAT02 model (Fairchild, 2001), was developed by fi tting all available datasets except the McCann data with the same structure as CMCCAT2000.…”
Section: Colour Inconstancy Index Cmccon02supporting
“…The CMCCAT2000 formula removes this problem by simplifying its structure. Sobagaki et al (1999) showed that the CMCCAT97 gives large errors for predicting corresponding colours under the very dim saturated yellow illumination used in one of the McCann experimental phases. Later, a new model, the CAT02 model (Fairchild, 2001), was developed by fi tting all available datasets except the McCann data with the same structure as CMCCAT2000.…”
Section: Colour Inconstancy Index Cmccon02supporting
“…They believed that this set of conditions can provide a particularly severe test of chromatic adaptation transforms. As shown by Sobagaki et al [8], the CMCCAT97 gives large errors for predicting corresponding colours under the very dim saturated yellow illumination used in one of the McCann experimental phases. Later, a new model, the CAT02 model [9], was developed by fitting all available data sets except the McCann data with the same structure as CMCCAT2000.…”
Section: Why Replace Cmccon97 By Cmccon02?mentioning
A colour inconstancy index, CMCCON02, is used for predicting the degree of colour inconstancy of a specimen defined by its spectral reflectance. CMCCON02 is different from the previously proposed CMCCON97 due to the replacement of the original chromatic adaptation transform (CMCCAT97) by CAT02. The latter is embedded in the CIE 2002 colour appearance model, CIECAM02. CAT02 is a simplified version of CMCCAT97 and gives more accurate predictions of the various experimental data sets. The CMCCON02 transform is in the process of being incorporated into ISO 105. This publication is sponsored by the Society's Colour Measurement Committee.
“…14 Similar comparisons have been reported for the combined CIECAT94 and CIELAB model 14 and for CIECAM97s. 15 A comparison of the three results (Kuo et al, CIECAT94ϩCELAB, 14 and CIECAM97s 15 ) on ͗D N ͘ and ͗RMS N ͘ suggests that the predictions using the F*G* operation based on Kuo et al had larger deviations from the CSAJ observations than did the other two models. However, we are not able to discuss these points further in this article.…”
Section: Predictions With Kuo Et Al F*g* Functionsmentioning
A new method is proposed for predicting corresponding colors from magnitude estimation data conducted under two adapting illuminants on the same group of object color samples. Called the F*G* method, it was applied under illuminants D65 and A to magnitude estimation data by Kuo et al. and Luo et al., a part of the LUTCHI data. Both derived F*G* equations were also applied in an experiment with the CSAJ data under illuminants D65 and A. Analyses of these experiments clarified two points: (1) the magnitude estimation method is inaccurate for predicting corresponding colors including with the Kuo et al. and Luo et al. data; and (2) unacceptable extrapolations had been made by Luo et al. in deriving their corresponding colors.
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