A Lattice Boltzmann Method for Image Denoising

作     者：Chang, Qianshun Yang, Tong 

作者机构：Chinese Acad Sci Inst Appl Math Acad Math & Syst Sci Beijing Peoples R China City Univ Hong Kong Dept Math Hong Kong Hong Kong Peoples R China 

出 版 物：《IEEE TRANSACTIONS ON IMAGE PROCESSING》 (IEEE Trans Image Process)

年 卷 期：2009年第18卷第12期

页      面：2797-2802页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：City University of Hong Kong, CityU, (7002129) National Natural Science Foundation of China, NSFC 

主　　题：Algorithm of denoising fast algorithm image restoration lattice Boltzmann method parallel algorithm 

摘      要：In this paper, we construct a Lattice Boltzmann scheme to simulate the well known total variation based restoration model, that is, ROF model. The advantages of the Lattice Boltzmann method include the fast computational speed and the easily implemented fully parallel algorithm. A conservative property of the LB method is discussed. The macroscopic PDE associated with the LB algorithm is derived which is just the ROF model. Moreover, the linearized stability of the method is analyzed. The numerical computations demonstrate that the LB algorithm is efficient and robust. Even though the quality of the restored images is slightly lower than those by using the ROF model, the restored images of the LB method are satisfactory. Furthermore, computational speed of the LB method is much faster than ROF model. In general, CPU time of the LB method for restored images is about one tenth of ROF model.