Clustering analysis as a basic tool for hyperspectral remote sensing image

被引：1
|
作者：
Xu, Han [1 ]
Li, Xiaojuan [1 ]
Gao, Xiaowei [2 ]
机构：
[1] Capital Normal Univ, Coll Resource Environm & Tourism, Beijing, Peoples R China
[2] ImageInfo Co LTD, Beijing, Peoples R China
来源：
MIPPR 2011: REMOTE SENSING IMAGE PROCESSING, GEOGRAPHIC INFORMATION SYSTEMS, AND OTHER APPLICATIONS | 2011年 / 8006卷
关键词：
clustering analysis; hyperspectral remote sensing; supervised/unsupervised classification; CLASSIFICATION;
D O I：
10.1117/12.902115
中图分类号：
TP7 [遥感技术];
学科分类号：
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要：
Clustering analysis groups data objects based on information only found in the data that describes the objects and the relationships. As it is a spatial method, more research are focused on remote sensing application recently. This paper presents comparison of two classic cluster algorithms used in hyperspectral remote sensing image classification and the results showed that the classification of maximum likelihood algorithm is better than ISODATA algorithm.
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页数：6
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