A Spatial Color Compensation Model Using Saturation-Value Total Variation

Color image enhancement is one of the most important tasks in image processing. In this paper, we focus on the red and/or blue attenuation problem that arises in underwater image enhancement. We propose and develop a novel spatial color compensation model based on saturation-value total variation (SV-TV). In the proposed model, the compensation of the red and/or blue attenuation is achieved by adding a fraction of the green channel to the red and/or blue channel. The fraction is determined by a spatially varying function, which is controlled by the TV regularization. In order to avoid overcompensation and too many color artifacts, we make use of the SV-TV to regularize the objective compensation result. We numerically apply the proximal alternating linearized mini-mization to solve the proposed minimization problem, and we give the convergence analysis of the proposed algorithm. Numerical examples are presented to demonstrate that the performance of the proposed color compensation model is better than that of other testing methods in terms of visual quality and certain criteria, such as peak signal-to-noise ratio (PSNR), structure similarity (SSIM), and CIEde2000 color difference.