Colour Gamut Mapping as a Constrained Variational Problem
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Conjoint analysis for evaluating parameterized gamut mapping algorithms
IEEE Transactions on Image Processing
ADICT: accurate direct and inverse color transformation
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Distributed Multi-Feature Recognition Scheme for Greyscale Images
Neural Processing Letters
Spatial colour gamut mapping by means of anisotropic diffusion
CCIW'11 Proceedings of the Third international conference on Computational color imaging
Full-Reference Image Quality Metrics: Classification and Evaluation
Foundations and Trends® in Computer Graphics and Vision
Gamut Mapping Spatially Varying Reflectance with an Improved BRDF Similarity Metric
Computer Graphics Forum
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Gamut mapping deals with the need to adjust a color image to fit into the constrained color gamut of a given rendering medium. A typical use for this tool is the reproduction of a color image prior to its printing, such that it exploits best the given printer/medium color gamut, namely the colors the printer can produce on the given medium. Most of the classical gamut mapping methods involve a pixel-by-pixel mapping and ignore the spatial color configuration. Recently proposed spatial-dependent approaches for gamut mapping are either based on heuristic assumptions or involve a high computational cost. In this paper, we present a new variational approach for space-dependent gamut mapping. Our treatment starts with the presentation of a new measure for the problem, closely related to a recent measure proposed for Retinex. We also link our method to recent measures that attempt to couple spectral and spatial perceptual measures. It is shown that the gamut mapping problem leads to a quadratic programming formulation, guaranteed to have a unique solution if the gamut of the target device is convex. An efficient numerical solution is proposed with promising results.