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基于模糊Bayes-Gauss判别法的遥感影像的聚类
引用本文: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].厦门水产学院学报,2011(2):154-158.
作者姓名:颜军  陈水利  吴云东
作者单位:[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
基金项目:福建省自然科学基金资助项目(A0810014); 福建省教育厅重点项目(JK2009017); 福建省科技厅青年人才创新基金项目(2009J05009); 厦门市科技计划项目(3502Z20093018)
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.

关 键 词:遥感影像  加权Fisher判别法  Bayes判别法  模糊Bayes-Gauss判别法

Remote Sensing Image Clustering Based on Fuzzy Bayes-Gauss Criterion
Authors:YAN Jun  CHEN Shui-li  WU Yun-dong
Institution:1.School of Science,Jimei University,Xiamen 361021,China; 2.Research Centre of Image Information Engineering,Jimei University,Xiamen 361021,China)
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.
Keywords:remote sensing image  weighted Fisher linear discriminant(FLD)  Bayes algorithm  fuzzy Bayes-Gauss criterion
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