Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (10): 23-25.DOI: 10.3778/j.issn.1002-8331.2009.10.008

• 博士论坛 • Previous Articles     Next Articles

Improved image denoising algorithm of PDEs based on fuzzy logic

SHI Zhen-gang1,2,GAO Li-qun2   

  1. 1.College of Information Science and Engineering,Shenyang Ligong University,Shenyang 110168,China
    2.College of Information Science and Engineering,Northeastern University,Shenyang 110004,China
  • Received:2008-12-17 Revised:2009-02-09 Online:2009-04-01 Published:2009-04-01
  • Contact: SHI Zhen-gang



  1. 1.沈阳理工大学 信息科学与工程学院,沈阳 110168
    2.东北大学 信息科学与工程学院,沈阳 110004
  • 通讯作者: 石振刚

Abstract: In research of image denoising,in order to remove noise effectively and preserve edges and key details,an effective image denoising algorithm based on fuzzy logic PDEs is proposed in this paper.This algorithm combines the fuzzy logical with the Perona-Malik method.This algorithm builds a new diffusion coefficient in partial derivative equation with the fuzzy membership between the image gradient and the corresponding smooth regions.By defining reasonable fuzzy membership function,the algorithm is based upon a selective and improved diffusion coefficient and performed adaptively towards different gradients.Simulation experiments show the algorithm can effectively reduce the noises of the image,and its results needn’t to be adjusted,which can enhance the precision of edge orientation.

Key words: noisy image, partial derivative equation, diffusion coefficient, fuzzy logic, fuzzy membership function

摘要: 在研究图像噪声过滤时,为了既有效地去除噪声,又能够较好地保持图像边缘和重要的细节信息,将模糊逻辑思想与PM方法相结合,提出了一种对噪声图像更有效的基于模糊逻辑的偏微分方程去噪算法。该算法把PM方法中扩散方程的扩散系数看作像素梯度对于图像平滑区域的模糊隶属度函数,并通过定义合理的模糊隶属度函数,使得对不同的像素梯度大小采用不同的扩散系数。仿真实验表明,此算法在去除噪声的同时,能更好地保持图像的边缘细节,具有较好的处理效果。

关键词: 噪声图像, 偏微分方程, 扩散系数, 模糊逻辑, 模糊隶属度函数