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Proceedings Paper

Clustering analysis as a basic tool for hyperspectral remote sensing image
Author(s): Han Xu; Xiaojuan Li; Xiaowei Gao
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Paper Abstract

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.

Paper Details

Date Published: 23 November 2011
PDF: 6 pages
Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 800619 (23 November 2011); doi: 10.1117/12.902115
Show Author Affiliations
Han Xu, Capital Normal Univ. (China)
Xiaojuan Li, Capital Normal Univ. (China)
Xiaowei Gao, ImageInfo Co., Ltd. (China)


Published in SPIE Proceedings Vol. 8006:
MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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