Lattice Boltzmann method for vector image denoising

被引：0

作者：

Wang Z.-Q. ^{[1
,2
]}

Yan Z.-Z. ^{[1
]}

Zhang R. ^{[1
]}

Qian Y.-H. ^{[3
]}

机构：

[1] School of Communication and Information Engineering, Shanghai University

[2] Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, Guangdong Province

[3] Shanghai Institute of Applied Mathematics and Mechanics

来源：

Yingyong Kexue Xuebao/Journal of Applied Sciences | 2010年 / 28卷 / 05期

关键词：

Lattice Boltzmann model; Nonlinear diffusion; Partial differential equation; Vector image denoising;

D O I：

10.3969/j.issn.0255-8297.2010.05.008

中图分类号：

学科分类号：

摘要：

We present a new lattice Boltzmann method for vector image nonlinear diffusion by embedding vector image's edge feature into the relaxation parameter of the Lattice Boltzmann equation and designing high efficient equilibrium distributions. This overcomes the problems of poor efficiency and the difficulty in parallelization of the traditional numerical methods using nonlinear diffusion model for vector image denoising. To keep the algorithm stable, the method can iterate with large step to improve computation efficiency. Influence of equilibrium distribution on computation accuracy and efficiency is evaluated in the numerical simulation of second dimensional diffusion problem. To illustrate effectiveness of the method, color images contaminated by Gaussian noise and impulsive noise are tested. Experimental results and the analysis show that computation accuracy and efficiency of the proposed method are better than that of the traditional numerical method such as additive operator splitting (AOS) algorithm.

引用

页码：493 / 500

页数：7

共 10 条

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