A Color to Grayscale Conversion Considering Local and Global Contrast

Abstract

For the conversion of a color image to a perceptually plausible grayscale one, the global and local contrast are simultaneously considered in this paper. The contrast is measured in terms of gradient field, and the energy function is designed to have less value when the gradient field of the grayscale image is closer to that of original color image (called target gradient field). For encoding both of local and global contrast into the energy function, the target gradient field is constructed from two kinds of edges : one that connects each pixel to neighboring pixels and the other that connects each pixel to predetermined landmark pixels. Although we can have exact solution to the energy minimization in the least squares sense, we also present a fast implementation for the conversion of large image, by approximating the energy function. The problem is then reduced to reconstructing a grayscale image from the modified gradient field over the standard 4-neighborhood system, and this can be easily solved by the fast 2D Poisson solver. In the experiments, the proposed method is tested on various images and shown to give perceptually more plausible results than the existing methods.