Color Gamut Mapping Based on Image Fusion

Gamut mapping is a color transformation technique to solve a problem caused by mismatch of gamuts among imaging devices. One plausible goal of gamut mapping is to find a reproduction that is perceptually closest to the corresponding original image when an exact color matching is not possible. Most of the classical gamut mapping methods use colorimetric pixel-wise principles and ignore the spatial color configuration. The recently proposed spatial-dependent approaches are either based on heuristic assumptions or involve a high computational cost. In this paper, a new approach for image-dependent gamut mapping via image fusion is proposed. First, a measure to quantify the perceptual difference between images is presented, with which a divide and conquer scheme is employed to take image colors and spatial characteristics into account. Then a mapping fusion model is constructed to implement the method. Experiments show that the proposed algorithm gains obvious advantage than traditional ones, especially in color difference and image details.