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Proceedings Paper

Hyperspectral anomaly detection based on maximum likelihood method
Author(s): Edisanter Lo
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Paper Abstract

Detection of a subspace anomaly is an important application of hyperspectral imaging in remote sensing. Sub-space anomaly detection depends on the unknown dimension of the main background subspace. When the dimension is high, detection algorithms tend to have unsatisfactory performance. This paper proposes an anomaly detection algorithm that will continue to perform satisfactorily when the dimension is high.

Paper Details

Date Published: 29 July 2015
PDF: 6 pages
Proc. SPIE 9659, International Conference on Photonics Solutions 2015, 965914 (29 July 2015); doi: 10.1117/12.2196550
Show Author Affiliations
Edisanter Lo, Susquehanna Univ. (United States)

Published in SPIE Proceedings Vol. 9659:
International Conference on Photonics Solutions 2015
Surasak Chiangga; Sarun Sumriddetchkajorn, Editor(s)

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