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. Several measures to quantify, the perceptual difference between images have been proposed and applied to the gamut mapping problem. However most of the measures, such as average color difference, are applied on a pixel-wise basis and show poor correlation with human visual perception. This article describes a model of the perceptual image difference for a given pair of images which takes the human＇s contrast sensitivity into account and applies the model to a gamut mapping for generating a reproduction with minimum perceptual image difference. The model has a multispatial-frequency channel structure with tunable peak gains for each channel, which are determined by psychophysical experiments, so that the model output fits the observer＇s sensitivity to the image difference A gamut-mapped image with minimum perceptual image difference is obtained by an iterative minimization process. To evaluate the proposed method, subjective evaluation experiments are performed to construct ratio scalds that measure perceptual image difference of gamut-mapped reproductions generated by the proposed and pixel-wise methods. Results show that the reproductions by the proposed method are perceived as perceptually closest to the original, and the model＇s estimate of perceptual difference correlates better with the experimentally measured perceived image difference than other pixel-wise measures.