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A Numerical Minimization of Perceptual Error for the Linear Chromatic Adaptation Transform

In this paper, new sensors for the chromatic adaptation transform (CAT) are found. They have been obtained by the independent numerical minimization of 6 perceptual error metrics over 16 corresponding color pair (CCP) data sets, including Lam's set, using as starting point for the minimization 4 known and commonly used sensors. An analysis of their performances has shown that the best performance is always achieved by the sensors resulting from the minimization process over Lam's data set. Some of these performances are statistically equivalent to and even better than those obtained using the CMCCAT2000 and the nonlinear Bradford transforms. This result reinforces both the use of Lam's set as a good representation for the other CCP data sets, and the e orts mentioned in the literature towards the removal of the nonlinearity of the CAT of the CIECAM97 model.