Progressive line processing of global and local real-time anomaly detection in hyperspectral images-Reference-Cited by-同舟云学术

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Progressive line processing of global and local real-time anomaly detection in hyperspectral images

Published:2017-12-11 Issue:6 Volume:16 Page:2289-2303
ISSN:1861-8200
Container-title:Journal of Real-Time Image Processing
language:en
Short-container-title:J Real-Time Image Proc

Author:

Zhao Chunhui,Yao Xifeng

Funder

the National Natural Science Foundation of China

the Key Program of Heilongjiang Natural Science Foundation

the Program Excellent Academic Leaders of Harbin

Publisher

Springer Science and Business Media LLC

Subject

Information Systems

Link

http://link.springer.com/content/pdf/10.1007/s11554-017-0738-8.pdf

Reference28 articles.

1. Chang, C.-I.: Hyperspectral Imaging: Techniques for Spectral Detection and Classification. Kluwer Academic/Plenum Publishers, New York (2003)

2. Chang, C.-I.: Hyperspectral Data Processing: Algorithm Design and Analysis. Wiley, Hoboken (2013)

3. Reed, I.S., Yu, X.: Adaptive multiple-band CFAR detection of an optical pattern with unknown spectral distribution. IEEE Trans. Acoust. Speech Signal Process. 38(10), 1760–1770 (1990)

4. Taitano, Y.P., Geier, B.A., Bauer, K.W.: A locally adaptable iterative RX detector. J. Adv. Signal Process. 2010(1), 1–10 (2010)

5. Matteoli, S., Diani, M., Corsini, G.: A kurtosis-based test to efficiently detect targets placed in close proximity by means of local covariance-based hyperspectral anomaly detectors. In: Proceedings of the 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Lisbon, Portugal (2011)

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