Unsupervised Land Cover Classification Using H/α^^-/TP Space Applied to POLSAR Image Analysis(Sensing)
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概要
- 論文の詳細を見る
This paper takes full advantage of polarimetric scattering parameters and total power to classify polarimetric SAR image data. The parameters employed here are total power, polarimetric entropy, and averaged alpha angle (alphabar). Since these parameters are independent each other and represent all the scattering characteristics, they seem to be one of the best combinations to classify Polarimetric Synthetic Aperture Radar (POLSAR) images. Using unsupervised classification scheme with iterative Maximum Likelihood classifier, it is possible to decompose multi-look averaged coherency matrix with complex Wishart distribution effectively. The classification results are shown using Pi-SAR image data set comparing with other representative methods.
- 社団法人電子情報通信学会の論文
- 2004-06-01
著者
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Yamaguchi Yoshio
Niigata University
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Yamaguchi Yoshio
Faculty of Engineering, Niigata University
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Yamaguchi Y
Niigata Univ. Niigata Jpn
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Yamaguchi Y
Niigata Univ. Jpn
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YAMADA Hiroyoshi
Niigata University
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Yamaguchi Yoshio
Niigata Univ. Niigata Jpn
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YAMAGUCHI Yoshio
the Department of Information Engineering, Niigata University
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KIMURA Koji
Niigata University
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Yamaguchi Yoshio
Dept. Of Information Engineering Niigata University
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Yamaguchi Yoshio
Department Of Physics Tokai University
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Yamada Hiroyoshi
Dept. Of Information Engineering Niigata University
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Kimura K
Niigata University
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Yamada H
Faculty Of Engineering Niigata University
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Yamada Hiroyoshi
Niigata Univ. Niigata Jpn
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Yamaguchi Y
Faculty Of Engineering Niigata University
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Yamaguchi Y
Niigata University
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Yamada Hiroyoshi
The Department Of Information Engineering Niigata University
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YAMAGUCH Yoshio
the Faculty of Engineering, Niigata University
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Yamaguchi Yoshio
Dept.of Information Eng. Niigata University
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Yamaguchi Yoshio
Niigata Univ. Niigata‐shi Jpn
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YAMAGUCHI Yoshio
Department of Physics, Tokai University
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