A saturation-value histogram equalization model for color image enhancement

Abstract

In this paper, we propose and develop a novel variational histogram equalization framework for color image enhancement. The main idea is to propose a variational model containing an energy functional which leads to adjust the pixel values of an input image so that the resulting histogram of saturation and value components can be redistributed uniformly. In the proposed model, we make use of a mean brightness constraint term to guarantee the preservation of mean brightness information. The saturation-value total variation is incorporated for color correction and noise elimination in order to improve the image quality. Theoretically, the existence of the minimizer of the variational model and the convergence of the proposed algorithm are analyzed. Experimental results are shown to demonstrate the feasibility and effectiveness of the proposed model.