The equivalence of the anisotropic diffusion and HAAR wavelet shrinkage in 2-dimension in a given condition has been proved. The anisotropic wavelet shrinkage based on the equivalence combines the merits of wavelet shrinkage and anisotropic diffusion. In this paper

applying the anisotropic wavelet shrinkage to multiresolution image segmentation is researched

one improved method to multi-resolution anisotropic diffusion image segmentation method is proposed

which is a multi-resolution anisotropic wavelet shrinkage image segmentation method. The anisotropic wavelet shrinkage is used to diffuse the pixels in the image

and the gray level of the neighbor pixels in homogenous fields tend to become the same value along with the scale’s increase while keeping the edge as far as possible. The scale space stack based on scale is built

and the segmentation to object is accomplished. It is an unsupervised method. Comparison experiments show that the method can locate the edge of the object exactly while processing the internal inconsistency of fields effectively

and the homogenous fields are merged perfectly to implement segmentation. The convergence speed of the method is faster than the multi-resolution anisotropic diffusion image segmentation method.