Gamut mapping is the problem of transforming the colors of image or video content so as to fully exploit the color palette ofthe display device where the content will be shown, while preserving the artistic intent of the original content’s creator. In particular in thecinema industry, the rapid advancement in display technologies has created a pressing need to develop automatic and fast gamutmapping algorithms. In this paper we propose a novel framework that is based on vision science models, performs both gamut reductionand gamut extension, is of low computational complexity, produces results that are free from artifacts and outperforms state-of-the-artmethods according to psychophysical tests. Our experiments also highlight the limitations of existing objective metrics for the gamutmapping problem.

Thiswork has received funding from the European Union’sHorizon 2020 research and innovation programme undergrant agreement number 761544 (project HDR4EU) andunder grant agreement number 780470 (project SAUCE),and by the Spanish government and FEDER Fund, grantref. TIN2015-71537-P (MINECO/FEDER,UE). The work of J.Vazquez-Corral was supported by the Spanish governmentunder Grant IJCI-2014-19516