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应用科学学报 ›› 2010, Vol. 28 ›› Issue (4): 367-373.doi: 10.3969/j.issn.0255-8297.2010.04.007

• 信号与信息处理 • 上一篇    下一篇

图像非线性扩散去噪的格子波尔兹曼方法

王志强1， 严壮志1， 钱跃竑2   

  1. 1. 上海大学通信与信息工程学院，上海200072
    2. 上海大学上海市应用数学和力学研究所，上海200072
  • 收稿日期:2009-12-17 修回日期:2010-03-17 出版日期:2010-07-23 发布日期:2010-07-23
  • 作者简介:严壮志，教授，博导，研究方向：生物医学图像与信息处理，E-mail: zzyan@shu.edu.cn

Nonlinear Diffusion for Image Denoising Using Lattice Boltzmann Method

WANG Zhi-qiang1, YAN Zhuang-zhi1, QIAN Yue-hong2   

  1. 1. School of Communication and Information Engineering, Shanghai University, Shanghai 200072, China
    2. Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai 200072, China
  • Received:2009-12-17 Revised:2010-03-17 Online:2010-07-23 Published:2010-07-23

PDF

2046

被引次数

10

摘要：

针对传统图像去噪非线性扩散模型及其算法效率低和难以并行化的缺点，该文在格子波尔兹曼方程的松弛因子中引入图像边缘特征以实现图像的非线性扩散去噪. 在保证算法稳定的情况下能进行大步长迭代运算以提高处理效率，且适用于并行化计算. 实验结果和分析表明，该文所提出的方法与加性分裂算法相比能够获得更好的去噪质量，其计算精度和效率都优于加性分裂算法.

关键词: 图像去噪, 格子波尔兹曼方法, 非线性扩散, 偏微分方程

Abstract:

To overcome poor efficiency and difficulty in parallelization of traditional numerical method for image denoising with a nonlinear diffusion model, we propose a new lattice Boltzmann method to embed the image edge features into the relaxation parameters of the lattice Boltzmann equation for image nonlinear diffusion. While keeping stability in calculation, the algorithm allows large steps in the iteration so that the computation efficiency is improved. Additionally, the algorithm is easy to be parallelized. Experiment results show that the lattice Boltzmann method has better quality, accuracy and algorithmic efficiency in image denoising as compared to the additive operator splitting (AOS) algorithm.

Key words: image denoising, lattice Boltzmann method, nonlinear diffusion, partial differential equation

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