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聚类分析用于序列SAR干涉像对选取

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  • 武汉大学遥感信息工程学院,武汉430079
潘斌,博士,副教授,研究方向:SAR遥感及应用,E-mail: panbin@whu.edu.cn;舒宁,教授,博导,研究方向:高光谱遥 感及微波遥感,E-mail: nshuwu@126.com

收稿日期: 2010-07-22

  修回日期: 2010-09-09

  网络出版日期: 2010-09-26

基金资助

国家“863”高技术研究发展计划基金(No.2009AA12Z141);测绘遥感信息工程国家重点实验室专项基金资助

Cluster Analysis for Selection of Time Series Interferometric SAR Imagery

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  • School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

Received date: 2010-07-22

  Revised date: 2010-09-09

  Online published: 2010-09-26

摘要

 该文分析了干涉像对选取过程,提出一种利用聚类分析进行序列SAR干涉像对选取的方法. 选择合适的去相干因素构建特征空间,将序列SAR影像所有干涉组合的去相干因素映射到该特征空间,从而将干涉像对选取问题转换为特征空间的聚类分析. 根据干涉像对选取原则设计合适的聚类方法对去相干因素进行聚类,聚类结果对应于符合要求的干涉像对,实现序列SAR干涉像对的选取. 实验结果表明该方法简单有效.

本文引用格式

潘斌, 舒宁 . 聚类分析用于序列SAR干涉像对选取[J]. 应用科学学报, 2010 , 28(5) : 501 -506 . DOI: 10.3969/j.issn.0255-8297.2010.05.009

Abstract

Abstract: We propose a method to select interferometric SAR pairs for time series differential SAR Interferometry (D-InSAR) by using cluster analysis. In this approach, proper decorrelation factors are selected to construct a feature space, and decorrelation factors of all possible SAR interferometric pairs are mapped to the space. Thus, interferometric pair selection is converted to a problem of feature space clustering. A cluster algorithm is developed based on the principle of interferometric pair selection. This way, selected interferometric images corresponding to the clustering result are obtained. Experimental results show that the proposed approach is simple and effective.

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