Abstract: Spatial proximity and similarity of the pixel values of bilateral filter in the filter based on
the calculation of the range of filter kernel coefficient is susceptible to noise interference. When the
noise level is high, the direct use of noise image to guide the kernel weight computation program is
not feasible. Therefore, in this paper, the anisotropic total variation and bilateral filtering are
combined. Firstly, the image is processed by the anisotropic total variation model, and the result
image with rich edge structure information is obtained. Then the calculation results of image as a
guide bilateral filtering image to guide the range of filter kernel coefficient. In order to ensure the
stability of the algorithm, the above process is iterated. In addition, in order to improve the
computational efficiency of the anisotropic total variation model, the Split Bregman iterative
algorithm is introduced to accelerate the computation. The experimental results show that the
proposed algorithm can preserve more edge information while denoising.

Key words: image denoising, bilateral filter, anisotropic total variation, Split Bregman iterative method;
structure preserve capability