|本期目录/Table of Contents|

[1]颜军,陈水利,吴云东.基于模糊Bayes-Gauss判别法的遥感影像的聚类[J].集美大学学报(自然科学版),2011,16(2):154-158.
 YAN JunCHEN Shui-liWU Yun-dong.Remote Sensing Image Clustering Based on Fuzzy Bayes-Gauss Criterion[J].Journal of Jimei University,2011,16(2):154-158.
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《集美大学学报(自然科学版)》[ISSN:1007-7405/CN:35-1186/N]

卷:
第16卷
期数:
2011年第2期
页码:
154-158
栏目:
数理科学与信息工程
出版日期:
2011-03-25

文章信息/Info

Title:
Remote Sensing Image Clustering Based on Fuzzy Bayes-Gauss Criterion
作者:
颜军1陈水利12吴云东12
(1.集美大学理学院,福建 厦门 361021;2.集美大学影像信息工程技术研究中心,福建 厦门 361021)
Author(s):
YAN Jun1CHEN Shui-li12WU Yun-dong12
(1.School of Science,Jimei University,Xiamen 361021,China;2.Research Centre of Image Information Engineering,Jimei University,Xiamen 361021,China)
关键词:
遥感影像加权Fisher判别法Bayes判别法模糊Bayes-Gauss判别法
Keywords:
remote sensing imageweighted Fisher linear discriminant(FLD)Bayes algorithm fuzzy Bayes-Gauss criterion
分类号:
-
DOI:
-
文献标志码:
-
摘要:
针对Fisher线性判别法和传统的Bayes判别方法在遥感影像聚类问题研究中存在的不足,提出一种以隶属度代替先验概率的模糊Bayes-Gauss聚类算法,并将此算法应用于真彩色(RGB)图像中的草地、道路、裸土地和建筑物的聚类.实验结果表明,本算法在聚类中与Fisher线性判别法和传统Bayes判别法相比,具有精确度较高、误识率和拒识率较低、适用性较强的特点
Abstract:
In face of the shortcomings of the Fisher linear discriminant method and the traditional Bayesian algorithm in remote sensing image clustering,a new kind of fuzzy Bayes-Gauss clustering method was proposed by using fuzzy membership functions instead of priori probability.And the new algorithm was applied to the clustering of grasses,bare land,roads and buildings in True Color(RGB).The results of experiments showed that the new algorithm for clustering had higher precision,lower false accept rate and false reject rate,and stronger applicability advantages,compared with the weighted Fisher linear discriminant and traditional Bayes algorithm

参考文献/References:

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备注/Memo

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更新日期/Last Update: 2018-06-13