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Space Sensitive Color Gamut Mapping: A Variational Approach
Kimmel, Ron; Shaked, Doron; Elad, Michael; Sobel, Irwin
Keyword(s): gamut mapping; retinex algorithm; calculus of variations; robust reconstruction
Abstract: Gamut mapping is a method to modify a representation of a color image to fit into a constrained color space of a given rendering medium. A laser-jet color printer that attempts to reproduce a color image on a regular paper would have to map the photographed picture colors in a given color range, also known as the image 'color gamut', into the given printer/page color gamut. 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. Note that spatially varying gamut mapping is inherently image dependent. We present a new variational approach for space dependent gamut mapping. The approach presents a new measure for the problem, and is closely related to a recent variational framework for Retinex. We link our method to recent measures that attempt to couple spectral and spatial perceptual measures. We show that the solution to our formulation of the problem is unique if the gamut of the target device is convex. A quadratic programming efficient numerical solution is proposed, with real-time promising results.
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