Robust Contrast Enhancement via Graph-Based Cartoon-Texture Decomposition

Abstract

In this paper, we propose a robust contrast enhancement algorithm based on cartoon and texture layer decomposition. Specifically, the cartoon layer is expected to be generally smoothing but with sharp edges at the foreground and background boundaries, for which we propose a quadratic form of graph total variation (GTV) as the prior to promote signal smoothness along graph structure. For the texture layer, a reweighted GTV is tailored to remove noises while preserving true image details. Finally, an optimization objective function is formulated, which casts image decomposition, contrast enhancement and noise reduction into a unified framework. We propose an efficient algorithm to solve it. Experimental results show that our generated images outperform state-of-the-art schemes noticeably in subjective quality evaluation.