Total Variation with Overlapping Group Sparsity for Removing Mixed Noise

Abstract

The total variation (TV) model has been used for removing the mixed additive and multiplicative noise. However, the restored images inevitably suffer from the staircase artifacts. In order to overcome this disadvantage, we propose two new variational models by combining the TV with overlapping group sparsity. Then the alternating direction method of multiplier (ADMM) is applied to solve the proposed models. Numerical experiments demonstrate that our methods are competitive with the state-of-the-art methods in visual and quantitative measures.