An Adaptive Strategy for the Restoration of Textured Images using Fractional Order Regularization  

作　　者：R.H.Chan A.Lanza S.Morigi F.Sgallari 

机构地区：[1]Department of Mathematics,The Chinese University of Hong Kong,Shatin,Hong Kong [2]Department of Mathematics–CIRAM,University of Bologna,Via Saragozza,8,Bologna,Italy [3]Department of Mathematics,University of Bologna,Piazza Porta San Donato,5,Bologna,Italy

出　　处：《Numerical Mathematics(Theory,Methods and Applications)》2013年第1期276-296,共21页高等学校计算数学学报（英文版）

基　　金：This work has been partially supported by MIUR-Prin 2008,ex60%project by University of Bologna"Funds for selected research topics"and by GNCS-INDAM.

摘　　要：Total variation regularization has good performance in noise removal and edge preservation but lacks in texture restoration.Here we present a texture-preserving strategy to restore images contaminated by blur and noise.According to a texture detection strategy,we apply spatially adaptive fractional order diffusion.A fast algorithm based on the half-quadratic technique is used to minimize the resulting objective function.Numerical results show the effectiveness of our strategy.

关 键 词：Ill-posed problem DEBLURRING fractional order derivatives regularizing iterative method 

分 类 号：TN9[电子电信—信息与通信工程]