The weighting function for lightness in the CIE94 color-difference model

We have tested the potential improvement achieved by the CIE94 color-difference model [CIE Publication 116–1995] when a linear function of lightness (SL = K1 + K2 L*) is introduced as a weighting function for the lightness difference ΔL*. Our analyses are based on experimental results previously obtained using object colors and visual colorimeters; new experimental results are not reported here. For the RIT-Dupont dataset [Color Res. Appl. 16, 297–316, 1991], the optimal values of the linear function tested are K1 = 1.02; K2 = 0.001, in excellent agreement with the proposal of the CIE94 model: K1 = 1.0; K2 = 0. However, for the dataset of Coates et al. [J. Soc. Dyers Colour. 97, 179–183, 1981], the best predictions were obtained using K1 = 0.5; K2 = 0.008, improving the results obtained by CMC(l:c) or BFD(l:c). These last values differ by a factor two from the proposal K1 = 1.0; K2 = 0.017 made in another recent study [Color Res. Appl. 19, 273–276, 1994]. Parametric factors, such as the texture of the samples and the lightness of the background, appear to be the main causes of the discrepancies found between the best weighting function for lightness, using different experimental datasets. While new experimental results are reported to clarify this problem, the present results support the proposal made by the CIE94 model, suggesting that the lightness-dependence correction can be considered as nonrobust and related to local parametric effects. © 1996 John Wiley & Sons, Inc.