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Remote Sensing Technology and Application  2008, Vol. 23 Issue (3): 341-345    DOI: 10.11873/j.issn.1004-0323.2008.3.341
article     
Study of Classification by Support Vector Machine on Synthetic Aperture Radar Image
TANG Jing-tian1,HU Dan1,GONG Zhi-min2
(1.Physical Information Engineering College of Central South University,Changsha 410083,China;2.Environment and Resource College of Wuhan University of Science and Technology,Wuhan 410083,China)
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Abstract  

Support Vector Machine (SVM) has excellent performance in classification.The Gray Level Co-occurrence Matrix (GLCM) is a promising method for texture analysis.Texture is an important feature in Synthetic Aperture Radar (SAR) image.So the arithmetic of texture classification by SVM was investigated, using GLCM to extract features.Compared to the method using image's gray information directly for SVM classifying, the experimental results show the feasibility and effectiveness of the new method.

Key words:  Hyperspectrum      Larch canopy      Photosynthetic pigment content      Health      Regression model     
Received:  10 November 2007      Published:  25 October 2011
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Cite this article: 

TANG Jing-tian,HU Dan,GONG Zhi-min. Study of Classification by Support Vector Machine on Synthetic Aperture Radar Image. Remote Sensing Technology and Application, 2008, 23(3): 341-345.

URL: 

http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2008.3.341     OR     http://www.rsta.ac.cn/EN/Y2008/V23/I3/341

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