Volume 5 Number 7 (Jul. 2010)
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JCP 2010 Vol.5(7): 1019-1026 ISSN: 1796-203X
doi: 10.4304/jcp.5.7.1019-1026

A Band Selection Method For Hyperspectral Images Using Choquet Fuzzy Integral

Fengchen Huang, Jing Ling, Aiye Shi, and Lizhong Xu
College of Computer and Information Engineering, Hohai University

Abstract—Hyperspectral remote sensing images provide richer information about materials than that of multispectral images. The new larger data volumes of hyperspectral sensors bring new challenges for traditional image processing techniques. Therefore, conventional classification methods could fail without employing dimension reduction preprocessing. The dimensional reduction methods can be totally divided into two classes: feature extraction and feature selection. In this paper, a new feature selection method for hyperspectral images is proposed, which colligates the information entropy, classification separability and correlation coefficients with the Choquet fuzzy integral to select the bands. Experiments on the AVIRIS dataset show that the proposed method removes the redundant spectral bands effectively.

Index Terms—hyperspectral images, image classification, fuzzy integral, spectral band selection, remote sensing

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Cite: Fengchen Huang, Jing Ling, Aiye Shi, and Lizhong Xu, " A Band Selection Method For Hyperspectral Images Using Choquet Fuzzy Integral," Journal of Computers vol. 5, no. 7, pp. 1019-1026, 2010.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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