To solve the problem of few correct matching points and low registration accuracy in the registration process of optical remote-sensing images and SAR images,an optical and SAR image registration algorithm combining Perona-Malik (P-M) filtering with the improved Local Self Similarity (LSS) is proposed.Firstly,the anisotropic diffusion equation is used to filter the speckle noise in the SAR image.Secondly,as to the significant gray difference between images,the extracted features of local area are used to obtain the self-similar values of each direction,the feature direction of the main direction is determined,and a stable LSS feature descriptor is formed to register the image by using the feature gradient position direction.Experimental results show that the proposed algorithm is robust to the imaging differences between optical images and SAR images,while effectively preserving the edge information of the image.Compared with that of similar registration algorithms,the registration accuracy of the proposed algorithm is improved by nearly 20%.