A weighted split Bregman iteration for adaptive fractional order total variation model

Image denoising is an important branch in the process of image processing which has been widely used in various fields. This paper proposes a weighted split Bregman iteration (WSBI) algorithm for adaptive fractional order total variation model, which provides an effective method to deal with the image denoising problem. A weight coefficient w is added to the split Bregman iteration (SBI) algorithm. Compared with the ordinary SBI algorithm, this improved algorithm can achieve faster convergence and higher (PSNR) of the image by experiments. This algorithm also can well preserve the texture details of the image and avoid the staircase artifact.