Semi-blind image restoration based on Chan-Vese denoising model  

作　　者：王智峰 唐延东 

机构地区：[1]State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences

出　　处：《Chinese Optics Letters》2008年第6期405-407,共3页中国光学快报（英文版）

基　　金：the Knowledge Innovation Program of Chinese Academy of Sciences(No.07A1210101)

摘　　要：A semi-blind image restoration algorithm is proposed based on reduced non-convex approximation of Luminita Vese and Tony Chan＇s （C-V） denoising model. Compared with C-V denoising model, we modify the fidelity term and add a term on point spread function （PSF）. The function depends on two variables： the image function to be restored u and the standard deviation of Gaussian kernel to be estimated a. Then the problems consist in solving a system with two coupled equations. Compared with the Leah Bar＇s semi-blind image restoration model which must solve three coupled equations, our method only needs to solve two equations. Furthermore, the estimation of f by our algorithm is superior to Leah Bar＇s algorithm. The experimental results demonstrate that the proposed method is effective.A semi-blind image restoration algorithm is proposed based on reduced non-convex approximation of Luminita Vese and Tony Chan＇s （C-V） denoising model. Compared with C-V denoising model, we modify the fidelity term and add a term on point spread function （PSF）. The function depends on two variables： the image function to be restored u and the standard deviation of Gaussian kernel to be estimated a. Then the problems consist in solving a system with two coupled equations. Compared with the Leah Bar＇s semi-blind image restoration model which must solve three coupled equations, our method only needs to solve two equations. Furthermore, the estimation of f by our algorithm is superior to Leah Bar＇s algorithm. The experimental results demonstrate that the proposed method is effective.

关 键 词：Boolean functions Computer networks Image reconstruction Optical transfer function REPAIR RESTORATION 

分 类 号：O411[理学—理论物理]