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On Semiparametric Clutter Estimation for Ship Detection in Synthetic Aperture Radar Images
http://hdl.handle.net/10191/21744
http://hdl.handle.net/10191/21744ac99a0d2-04dd-4835-8d3a-4d699421b38c
名前 / ファイル | ライセンス | アクション |
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IEEETGRS_99_1-11.pdf (798.4 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2013-04-15 | |||||
タイトル | ||||||
タイトル | On Semiparametric Clutter Estimation for Ship Detection in Synthetic Aperture Radar Images | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | On Semiparametric Clutter Estimation for Ship Detection in Synthetic Aperture Radar Images | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Clutter estimation | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | copula | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | kernel density estimator (KDE) | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | ship detection | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | synthetic aperture radar (SAR) | |||||
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× Yang, Jian× 山口, 芳雄× Singh, Gulab× Park, Sang-Eun× Kobayashi, Hirokazu |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | The statistical behavior of the sea clutter in synthetic aperture radar (SAR) images is characterized by both the marginal distribution and spatial correlation. However, simultaneous modeling of the joint information remains a difficult job because of the non-Gaussian clutter nature. In this paper, a semiparametric approach is proposed for addressing this problem with the two-fold purpose. First, we investigate the applicability of the nonparametric kernel density estimator (KDE) for marginal distribution estimation of the SAR clutter and show that the KDE is most applicable in the log-intensity domain. Second, we propose to separately estimate the underlying correlation structure with a copula approach and show that the Gaussian copula is a sufficiently accurate model. Consequently, the KDE together with the Gaussian copula, offers a full characterization of the joint probability distribution, based on which a quadratic detector of null distribution is governed by the well-known chi-square law can be conveniently designed for constant false alarm rate (CFAR) detection. In the experiment, results with both simulated and real SAR data demonstrate that, compared with the single-point detector using only the marginal distribution, the proposed method, which incorporates spatial correlation, significantly improves the detection performance with regard to either the receiver operating characteristic (ROC) curve or detected target pixels. The tradeoff, however, lies in a loss of false alarm rate (FAR) control resulting from increased uncertainty in estimating higher dimensional distributions. | |||||
書誌情報 |
IEEE transactions on geoscience and remote sensing en : IEEE transactions on geoscience and remote sensing 巻 51, 号 5, p. 3170-3180, 発行日 2013-05 |
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出版者 | ||||||
出版者 | IEEE | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 01962892 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA00231483 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | info:doi/10.1109/TGRS.2012.2218659 | |||||
権利 | ||||||
権利情報 | ©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. | |||||
著者版フラグ | ||||||
値 | author |