Nonlocal total variation models for multiplicative noise removal using split Bregman iteration

In this paper, the nonlocal total variation (TV) norm is employed for multiplicative noise removal. A main advantage of nonlocal TV norm over classical TV norm is the superiority in dealing with better textures and repetitive structures. Split Bregman iterations are used to implement the proposed models. What is more, to improve the performance of one of our models, we use the Bregman iteration as in the TV denoising model. A set of experiments show that the proposed methods yield better results than some other methods.