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Three-Component Power Decomposition for Polarimetric SAR Data Based on Adaptive Volume Scatter Modeling
http://hdl.handle.net/10191/29711
http://hdl.handle.net/10191/29711afb55f7a-ac5a-4072-9544-229b4015fa34
名前 / ファイル | ライセンス | アクション |
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remotesensing-04-01559.pdf (1.1 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2014-09-01 | |||||
タイトル | ||||||
タイトル | Three-Component Power Decomposition for Polarimetric SAR Data Based on Adaptive Volume Scatter Modeling | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Three-Component Power Decomposition for Polarimetric SAR Data Based on Adaptive Volume Scatter Modeling | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | polarimetric SAR | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | power decomposition | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | adaptive volume scattering model | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Cui, Yi
× Cui, Yi× Yamaguchi, Yoshio× Yang, Jian× Park, Sang-Eun× Kobayashi, Hirokazu× Singh, Gulab |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | In this paper, the three-component power decomposition for polarimetric SAR (PolSAR) data with an adaptive volume scattering model is proposed. The volume scattering model is assumed to be reflection-symmetric but parameterized. For each image pixel, the decomposition first starts with determining the adaptive parameter based on matrix similarity metric. Then, a respective scattering power component is retrieved with the established procedure. It has been shown that the proposed method leads to complete elimination of negative powers as the result of the adaptive volume scattering model. Experiments with the PolSAR data from both the NASA/JPL (National Aeronautics and Space Administration/Jet Propulsion Laboratory) Airborne SAR (AIRSAR) and the JAXA (Japan Aerospace Exploration Agency) ALOS-PALSAR also demonstrate that the proposed method not only obtains similar/better results in vegetated areas as compared to the existing Freeman-Durden decomposition but helps to improve discrimination of the urban regions. | |||||
書誌情報 |
Remote Sensing en : Remote Sensing 巻 4, 号 6, p. 1559-1572, 発行日 2012-05 |
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出版者 | ||||||
出版者 | MDPI | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 20724292 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | info:doi/10.3390/rs4061559 | |||||
権利 | ||||||
権利情報 | © 2012 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). | |||||
著者版フラグ | ||||||
値 | publisher |