A Space-Adaptive Regularization Approach for Blind Image Restoration
一种空间自适应正则化图象盲复原算法

A new space-adaptive regularization method for blind image restoration, which combines the idea of priori blur identification is presented. This new technique first identifies the point spread function(PSF) by using alternating minimization iterative algorithm. Then it restores the image based on the identified PSF using anisotropic regularization. The main difficulty in blind image restoration is insufficient information, which demands full utilization of priori knowledge of image itself and imaging system. This algorithm utilizes the piecewise smoothness of both the image and the PSF, and it simultaneously makes use of the concept of anisotropic diffusion, which carries out space adaptive regularization according to the orientations of the image and the PSF. This new method's efficiency is demonstrated by numerically blurred images. It can get better restoration images than space adaptive regularization(SAR) method, and converge faster than space adaptive anisotropic regularization(SAAR) method