期刊
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
卷 8, 期 6, 页码 2523-2533出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTARS.2015.2437073
关键词
Anomaly detection (AD); hyperspectral imagery; joint sparse representation (JSR); robust background estimation
类别
资金
- National Basic Research Program of China (973 Program) [2011CB707105]
- National Natural Science Foundation of China [61201342, 41431175, 61102104]
- Open Research Fund of Key Laboratory of Digital Earth, Chinese Academy of Sciences
In this paper, we propose a hyperspectral image anomaly detection model by the use of background joint sparse representation (BJSR). With a practical binary hypothesis test model, the proposed approach consists of the following steps. The adaptive orthogonal background complementary subspace is first estimated by the BJSR, which adaptively selects the most representative background bases for the local region. An unsupervised adaptive subspace detection method is then proposed to suppress the background and simultaneously highlight the anomaly component. The experimental results confirm that the proposed algorithm obtains a desirable detection performance and outperforms the classical RX-based anomaly detectors and the orthogonal subspace projection-based detectors.
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