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M变换在NOAA/AVHRR数据变化检测中的应用
引用本文:朱攀,廖明生,杨杰,刘良明.M变换在NOAA/AVHRR数据变化检测中的应用[J].武汉大学学报(信息科学版),2000,25(2).
作者姓名:朱攀  廖明生  杨杰  刘良明
作者单位:武汉测绘科技大学测绘遥感信息工程国家重点实验室,武汉市珞喻路129号,430079
基金项目:国家测绘局测绘科技发展基金!编号99008
摘    要:将基于典型相关分析的正交变换的基础理论用于NOAA/AVHRR数据的多元变化检测 ,对具体实施步骤进行了深入的探讨 ,并对部分中间结果进行了分析。实验表明 ,该方法应用于NOAA/AVHRR数据的多元变化检测具有明显的优势 ,克服了传统方法存在的缺陷 ,具有良好的应用前景。

关 键 词:典型变换  NOAA/AVHRR数据  多元变化检测  M变换

M Transformation Used in Multivariate Change Detection of NOAA/AVHRR Data
ZHU Pan,LIAO Mingsheng,YANG Jie,LIU Liangming.M Transformation Used in Multivariate Change Detection of NOAA/AVHRR Data[J].Geomatics and Information Science of Wuhan University,2000,25(2).
Authors:ZHU Pan  LIAO Mingsheng  YANG Jie  LIU Liangming
Abstract:The fundamental theory of orthogonal transformation based on canonical correlation analysis is applied to multivariate change detection with NOAA/AVHRR data.With two multivariate satellite images covering the same geographic area acquired at different points in time as a random whole sample,the strategy transforms two sets of random variables into one set of new random multivariate through the so_called canonical transformation introduced in the paper. It is tested in the middle reaches of Yangzi river where a great and heavy flood was caused during the period of time from July to August in 1998.The purpose of this experiment is to investigate what kinds of changes happened in this area from September,1996 to August,1998.At the same time,the experiments of the other methods for change detection have been conducted,comparing the result of the method presented in this paper.By comparison the experimental result shows the fact that the method based on canonical correlation analysis is exactly creditable and effective not only for clearly detecting water changes caused by flood,but also other changes such as vegetation,cloud,and so on.But with other methods,such as simple image difference and principal component analysis,it is difficult to distinguish the changes between water and vegetation.
Keywords:canonical transformation  NOAA/AVHRR data  multivariate Change detection  M transformation
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