Fast algorithm for multiplicative noise removal

作     者：Shi, Baoli Huang, Lihong Pang, Zhi-Feng 

作者机构：Hunan Univ Coll Math & Econometr Changsha 410082 Hunan Peoples R China Hunan Univ Coll Math & Informat Sci Kaifeng 475004 Hunan Peoples R China Hunan Womens Univ Changsha 410000 Hunan Peoples R China 

出 版 物：《JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION》 (可视通信与图像显示杂志)

年 卷 期：2012年第23卷第1期

页      面：126-133页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：973 Program [2009CB326202] National Natural Science Foundation of China [11071060, 60835004] Higher Educational Institutions of Hunan Province [XJT2008-244] 

主　　题：Multiplicative noise Anisotropic total variation Maximum a posteriori Convex function Alternating minimization algorithm Proximal operator Gamma distribution Newton method 

摘      要：In this work, we consider a variational restoration model for multiplicative noise removal problem. By using a maximum a posteriori estimator, we propose a strictly convex objective functional whose minimizer corresponds to the denoised image we want to recover. We incorporate the anisotropic total variation regularization in the objective functional in order to preserve the edges well. A fast alternating minimization algorithm is established to find the minimizer of the objective functional efficiently. We also give the convergence of this minimization algorithm. A broad range of numerical results are given to prove the effectiveness of our proposed model. Crown Copyright (C) 2011 Published by Elsevier Inc. All rights reserved.