NDLI: Spatial information based support vector machine for hyperspectral image classification

Content Provider	IEEE Xplore Digital Library
Author	Bor-Chen Kuo Chih-Sheng Huang Chih-Cheng Hung Yu-Lung Liu I-Ling Chen
Copyright Year	2010
Description	Author affiliation: Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taiwan, R.O.C. (Bor-Chen Kuo; Chih-Sheng Huang; I-Ling Chen) \|\| School of Computing and Software Engineering, Southern Polytechnic State University, GA, U.S.A. (Chih-Cheng Hung) \|\| Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan, R.O.C. (Yu-Lung Liu)
Abstract	In this study, a novel spatial information based support vector machine for hyperspectral image classification, named spatial-contextual semi-supervised support vector machine $(SC^{3}SVM),$ is proposed. This approach modifies the SVM algorithm by using the spectral information and spatial-contextual information. The concept of $SC^{3}SVM$ is to utilize other information, obtain from the pixels of a neighborhood system in the spatial domain, to modify the effective of each patterns. Experimental results show a sound performance of classification on the famous hyperspectral images, Indian Pine site. Especially, the overall classification accuracy of whole hyperspectral image (Indian Pine site with 16 classes) is up to 96.4%, the kappa accuracy is up to 95.9%.
Starting Page	832
Ending Page	835
File Size	250325
Page Count	4
File Format	PDF
ISBN	9781424495658
ISSN	21537003
e-ISBN	9781424495665
e-ISBN	9781424495641
DOI	10.1109/IGARSS.2010.5651433
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Accuracy Hyperspectral imaging Training Classification algorithms Pixel spatial-contextual semi-supervised support vector machine spatial information hyperspectral image classification support vector machine
Content Type	Text
Resource Type	Article

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