Colour gamut mapping between small and large colour gamuts: Part I. gamut compression.

Abstract

This paper describes an investigation into the performance of different gamut compression algorithms (GCAs) in different uniform colour spaces (UCSs) between small and large colour gamuts. Gamut mapping is a key component in a colour management system and has drawn much attention in the last two decades. Two new GCAs, i.e. vividness-preserved (VP) and depth-preserved (DP), based on the concepts of 'vividness' and 'depth' are proposed and compared with the other commonly used GCAs with the exception of spatial GCAs since the goal of this study was to develop an algorithm that could be implemented in real time for mobile phone applications. In addition, UCSs including CIELAB, CAM02-UCS, and a newly developed UCS, Jzazbz, were tested to verify how they affect the performance of the GCAs. A psychophysical experiment was conducted and the results showed that one of the newly proposed GCAs, VP, gave the best performance among different GCAs and the Jzazbz is a promising UCS for gamut mapping.