Gamut Mapping for Pictorial Images

A psychophysical evaluation was performed to test the quality of several color gamut mapping algorithms. The task was to determine which mapping strategy produced the best matches to the original image. Observer preference was not considered. The algorithms consisted of both device dependent and image-dependent mappings. Three types of lightness scaling functions (linear compression, chroma weighted linear compression, and image dependent sigmoidal compression) and four types of chromatic mapping functions were tested (linear compression, knee-point compression, sigmoidlike compression, and clipping). The source and destination devices considered were a monitor and a plain-paper inkjet printer respectively. The results showed that, for all of the images tested, the algorithms that used image-dependent sigmoidal lightness remapping functions produced superior matches to those that utilized linear lightness scaling. In addition, the results support using chromatic compression functions that were closely related to chromatic clipping functions