HYPERSPECTRAL BAND SELECTION FROM THE SPECTRAL SIMILARITY PERSPECTIVE

被引：0

作者：

Li, Shijin ^{[1
]}

Zhu, Yuelong ^{[1
]}

Wan, Dingsheng ^{[1
]}

Feng, Jun ^{[1
]}

机构：

[1] Hohai Univ, Sch Comp & Informat, Nanjing 210098, Jiangsu, Peoples R China

来源：

2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2013年

关键词：

Hyperspectral image; band selection; shape similarity; search; CLASSIFICATION; ALGORITHM; SYSTEM; IMAGES;

D O I：

10.1109/IGARSS.2013.6721179

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：

This paper proposes a new technique for hyperspectral band selection from the spectral similarity perspective. Through a newly defined measure for band subset discriminativeness, class-specific important bands are retained which can preserve the spectral similarity of the samples from the same class and narrow down candidate band subset for the following search procedure. Then optimal search is performed in the aggregated band subset from all classes. Experiments on the Indian Pine benchmark data set have proved the efficiency and effectiveness of the proposed method.

引用

页码：410 / 413

页数：4

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