Compared with the image with Space-invariant Point Spread Function (SVPSF), the restoration of the image with SVPSF ,whose degradation function in the object domain is different from point to point, is more difficult because of the extraction, storage and calculation of massive PSFs. Fortunately, three methods have been proposed to solve the problems: coordinate transformation approaches, sectioned restoration methods and direct algorithms, which are aimed to reduce the data storage, decrease the computational complexity, and improve convergence rate. The paper summarizes the research on the reconstruction of the image with SVPSF in the history, and then points out the crucial problems of the development of the issue in the future. Moreover, a total variation majorization-minimization sectioned restoration algorithm based on gradient ringing metric image quality assessment is exhibited.