A New Image Restoration Model Based on the Adaptive Total Variation

Abstract

Traditional total variation model leads to an undesirable staircase effect and is hard to eliminate high frequency noises in image restoration. In this paper, to solve this problem, a novel image restoration model based on adaptive total variation is proposed. A gradient fidelity term is coupled with adaptive total variation model. In order to choose proper parameters, the parameter selection criteria are analyzed theoretically, and a simple scheme to demonstrate its validity is adopted experimentally. To make fair comparisons of performances of three models, the same numerical algorithm is used to solve partial differential equations. Experimental results illustrate that the new model not only preserves the edge and important details but also alleviates the staircase effect effectively.