一种基于粒子群算法的模糊隶属函数优化方法

计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (18): 84-86.

一种基于粒子群算法的模糊隶属函数优化方法

石振刚^1,2,高立群¹

1.东北大学　信息科学与工程学院,沈阳 110004
2.沈阳理工大学信息科学与工程学院,沈阳 110168

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-06-21 发布日期:2007-06-21
通讯作者: 石振刚

Method of membership function based on fuzzy theory by PSO algorithm optimized

SHI Zhen-gang^1,2,GAO Li-qun¹

1.College of Information Science and Engineering,Northeastern University,Shenyang 110004,China
2.College of Information Science and Engineering,Shenyang Ligong University,Shenyang 110168,China

Received:1900-01-01 Revised:1900-01-01 Online:2007-06-21 Published:2007-06-21
Contact: SHI Zhen-gang

摘要/Abstract

摘要： 在分析图像模糊增强算法对于隶属函数及其模糊区域选择方法不足的基础上,提出一种新的基于粒子群算法的模糊隶属函数优化方法。该方法给出一个新模糊熵的定义,这个新模糊熵定义不仅考虑到图像在模糊域中划分区域时随隶属函数变化而变化的情况,同时又考虑到图像在空域中划分区域时随隶属函数变化而变化的情况。这样就使得图像依照最大熵准则变换到模糊域更能够有效地反映图像的固有信息。另外,根据图像增强算法中使用double型数据类型的特点,采用改进粒子群优化算法寻求隶属函数的最优参数。将新算法应用于图像增强中,取得了优于现有大多数模糊增强算法的效果。

Abstract: In this paper,a new method of membership function based on fuzzy theory by PSO algorithm optimized is proposed by analyzing the deficiencies of traditional enhancement algorithm.A new entropy definition of a fuzzy set is proposed.The new entropy definition of a fuzzy set is not only related to the membership（fuzzy domain） but also related to the probability distribution （space domain）,it can respond to the variety of image input information.In addition,by quoting a novel Particle Swarm Optimization（PSO） algorithm to find the optimization parameters for membership.We use our novel algorithm to enhance image,we can get a better result than that of most fuzzy enhancement algorithm.

石振刚^1,2,高立群¹. 一种基于粒子群算法的模糊隶属函数优化方法[J]. 计算机工程与应用, 2007, 43(18): 84-86.

SHI Zhen-gang^1,2,GAO Li-qun¹. Method of membership function based on fuzzy theory by PSO algorithm optimized[J]. Computer Engineering and Applications, 2007, 43(18): 84-86.