Chromatic adaptation performance of different RGB sensors

Chromatic adaptation transforms are used in imaging systems to map image appearance to colorimetry under different illumination sources. In this paper, the performance of different chromatic adaptation transforms (CAT) is compared with the performance of transforms based on RGB primaries that have been investigated in relation to standard color spaces for digital still camera characterization and image interchange. The chromatic adaptation transforms studied are von Kries, Bradford, Sharp, and CMCCAT2000. The RGB primaries investigated are ROMM, ITU-R BT.709, and “prime wavelength” RGB. The chromatic adaptation model used is a von Kries model that linearly scales post-adaptation cone responses with illuminant dependent coefficients. The transforms were evaluated using 16 sets of corresponding color data. The actual and predicted tristimulus values were converted to CIELAB, and three different error prediction metrics, ELab, ECIE94, and ECMC(1:1) were applied to the results. One-tail Student-t tests for matched pairs were calculated to compare if the variations in errors are statistically significant. For the given corresponding color data sets, the traditional chromatic adaptation transforms, Sharp CAT and CMCCAT2000, performed best. However, some transforms based on RGB primaries also exhibit good chromatic adaptation behavior, leading to the conclusion that white-point independent RGB spaces for image encoding can be defined. This conclusion holds only if the linear von Kries model is considered adequate to predict chromatic adaptation behavior.