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  1. 060 工学部
  2. 10 学術雑誌論文
  3. 10 査読済論文
  1. 0 資料タイプ別
  2. 01 学術雑誌論文

On Semiparametric Clutter Estimation for Ship Detection in Synthetic Aperture Radar Images

http://hdl.handle.net/10191/21744
http://hdl.handle.net/10191/21744
ac99a0d2-04dd-4835-8d3a-4d699421b38c
名前 / ファイル ライセンス アクション
IEEETGRS_99_1-11.pdf IEEETGRS_99_1-11.pdf (798.4 kB)
Item type 学術雑誌論文 / Journal Article(1)
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

WEKO 5237

Cui, Yi

Search repository
Yang, Jian

× Yang, Jian

WEKO 5238

Yang, Jian

Search repository
山口, 芳雄

× 山口, 芳雄

WEKO 19

山口, 芳雄

Search repository
Singh, Gulab

× Singh, Gulab

WEKO 5240

Singh, Gulab

Search repository
Park, Sang-Eun

× Park, Sang-Eun

WEKO 5241

Park, Sang-Eun

Search repository
Kobayashi, Hirokazu

× Kobayashi, Hirokazu

WEKO 5242

Kobayashi, Hirokazu

Search repository
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
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.
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