Automatic, fast and perceptually accurate gamut mapping based on vision science models

Gamut mapping transforms colors of the original (image or video) content to the color palette of the display device with the simultaneous goals of (a) reproducing content accurately while preserving the artistic intent of the original content's creator and (b) exploiting the full color rendering potential of the target display device. The rapid advancement in display technologies has created a pressing need to develop automatic and fast gamut mapping algorithms that can deal with imagery intended for both conventional and emerging displays. In this paper, we propose a novel framework based on retinal and color perception models from vision science that offers a functionality to perform both gamut reduction and gamut extension, while preserving hue and taking into account the analysis of the colors of the input image. We evaluate the performance of the proposed framework visually and by using a perceptually-based error metric, according to which the gamut-mapped results of our framework outperform those of the state-of-the-art methods.