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Matched Shrunken Cone Detector (MSCD): Bayesian Derivations and Case Studies for Hyperspectral Target Detection
http://hdl.handle.net/2241/00148343
http://hdl.handle.net/2241/0014834316aa9fd8-aa7e-48ca-8450-ffd794d48c4b
名前 / ファイル | ライセンス | アクション |
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IEEETIP_26-11 (2.8 MB)
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Item type | Journal Article(1) | |||||
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公開日 | 2017-09-26 | |||||
タイトル | ||||||
タイトル | Matched Shrunken Cone Detector (MSCD): Bayesian Derivations and Case Studies for Hyperspectral Target Detection | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Wang, Ziyu
× Wang, Ziyu× Zhu, Rui× Fukui, Kazuhiro× Xue, Jing-Hao |
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著者別名 |
福井, 和広
× 福井, 和広 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Hyperspectral images (HSIs) possess non-negative properties for both hyperspectral signatures and abundance coefficients, which can be naturally modeled using cone-based representation. However, in hyperspectral target detection, cone-based methods are barely studied. In this paper, we propose a new regularized cone-based representation approach to hyperspectral target detection, as well as its two working models by incorporating into the cone representation l2-norm and l1-norm regularizations, respectively. We call the new approach the matched shrunken cone detector (MSCD). Also important, we provide principled derivations of the proposed MSCD from the Bayesian perspective: we show that MSCD can be derived by assuming a multivariate half-Gaussian distribution or a multivariate half-Laplace distribution as the prior distribution of the coefficients of the models. In the experimental studies, we compare the proposed MSCD with the subspace methods and the sparse representation-based methods for HSI target detection. Two real hyperspectral data sets are used for evaluating the detection performances on sub-pixel targets and full-pixel targets, respectively. Results show that the proposed MSCD can outperform other methods in both cases, demonstrating the competitiveness of the regularized cone-based representation. | |||||
書誌情報 |
IEEE transactions on image processing 巻 26, 号 11, p. 5447-5461, 発行日 2017-11 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1057-7149 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA10821122 | |||||
PubMed番号 | ||||||
識別子タイプ | PMID | |||||
関連識別子 | 28816671 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1109/TIP.2017.2740621 | |||||
権利 | ||||||
権利情報 | This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/ | |||||
著者版フラグ | ||||||
値 | publisher | |||||
出版者 | ||||||
出版者 | IEEE |