Dimension reduction of remote sensing images by incorporating spatial and spectral properties

被引：9
|
作者：
Dianat, R. [1 ]
Kasaei, S. [1 ]
机构：
[1] Sharif Univ Technol, Dept Comp Engn, Image Proc Lab, Tehran, Iran
来源：
AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS | 2010年 / 64卷 / 08期
关键词：
Dimension reduction; Remote sensing; Image analysis;
D O I：
10.1016/j.aeue.2009.10.001
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A new and efficient dimension reduction method is introduced in this paper. The proposed method, almost the same as the well-known principal component analysis (PCA) method, enjoys the properties of uncorrelatedness of resulting components and orthogonality of transform coefficients. In addition, by incorporating spatial and spectral properties among image pixels, the method obtains more accurate classification results with less computational cost. (C) 2010 Published by Elsevier GmbH.
引用
收藏
页码：729 / 732
页数：4
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