Using Similarity Parameters for Supervised Polarimetric SAR Image Classification (Regular section)
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概要
- 論文の詳細を見る
In this paper, a new method is proposed for supervised classification of ground cover types by using polarimetric synthetic aperture radar (SAR) data. The concept of similarity parameter between two scattering matrices is introduced for characterizing target scattering mechanism. Four similarity parameters of each pixel in image are used for classification. They are the similarity parameters between a pixel and a plane, a dihedral, a helix and a wire. The total received power of each pixel is also used since the similarity parameter is independent of the spans of target scattering matrices. The supervised classification is carried out based on the principal component analysis. This analysis is applied to each data set in image in the feature space for getting the corresponding feature transform vector. The inner product of two vectors is used as a distance measure in classification. The classification result of the new scheme is shown and it is compared to the results of principal component analysis with other decomposition coefficients, to demonstrate the effectiveness of the similarity parameters.
- 社団法人電子情報通信学会の論文
- 2002-12-01
著者
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Xu J
Institute Of Advanced Materials Fudan University
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Yang Jian
Department of Electronic Engineering, Tsinghua University
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Yang J
Department Of Materials Physics And Energy Engineering Graduate School Of Engineering Nagoya Univers
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Yang J
Tsinghua Univ. Beijing Chn
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Yang Jian
Nagoya Univ. Nagoya Jpn
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Wang Chao
Key Laboratory For Radiation Beam Technology And Materials Modification Institute Of Low Energy Nucl
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Yang Jian
Department Of Materials Physics And Energy Engineering Graduate School Of Engineering Nagoya Univers
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Xu Jun
Liquid Crystal Institute And Graduate School Of Engineering Science Tokyo University Of Science
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Xu J
Akita Univ. Akita Jpn
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Xu J
National Inst. Advanced Industrial Sci. And Technol. (aist) Ibaraki Jpn
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Wang Chao
Institute Of Remote Sensing Applications Chinese Academy Of Sciences
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XU Junyi
Department of Electronic Engineering, Tsinghua University
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PENG Yingning
Department of Electronic Engineering, Tsinghua University
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LIOU Yuei-An
Center for Space and Remote Sensing Research, National Central University
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PENG Yingning
the Department of Electronic Engineering, Tsinghua University
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Yang Jian
Graduate School Of Engineering Nagoya University
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Peng Y
The Department Of Electronic Engineering Tsinghua University
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Peng Y‐n
Tsinghua Univ. Beijing Chn
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Yang Jian
Department Of Cardiology Renmin Hospital Of Wuhan University
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Peng Yingning
Department Of Electronic Engineering Tsinghua University
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Liou Yuei-an
Center For Space And Remote Sensing Research National Central University
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Liou Yuei-an
Center For Space And Remote Sensing Research And Institute Of Space Sciences National Central Univer
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Wang Chao
Institute Of Genetics And Developmental Biology Chinese Academy Of Sciences
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Yang Jian
Department Of Cardiology Daping Hospital The Third Military Medical University
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Yang J
Department Of Materials Physics And Energy Engineering Graduate School Of Engineering Nagoya Univers
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Yang Jian
Department Of Anesthesiology University Of Florida College Of Medicine
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Wang Chao
Institute for Computational Materials Science, School of Physics and Electronics, Henan University, Kaifeng 475004, China
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