Color image multiplicative noise and blur removal by saturation-value total variation

摘要

In this paper, we propose and develop a novel Saturation-Value Total Variation (SVTV) model for multiplicative noise and blur removal of color images. In the proposed model, SVTV regularization term is applied to model the target color image in HSV color space instead of RGB color space, and the fidelity term is well-adapted to multiplicative noise. We investigate into the existence and uniqueness of the minimizer of the proposed minimization problem. We study and show the convergence of an implicit scheme of the associated evolution problem for the numerical solution of the proposed SVTV model. Numerical examples are presented to demonstrate the performance of the proposed SVTV model is significantly better than that of other testing methods in terms of some criteria such as PSNR, SSIM and S-CIELAB color error.