Hyperspectral anomaly detection based on maximum likelihood method

Edisanter Lo

doi:10.1117/12.2196550

29 July 2015 Hyperspectral anomaly detection based on maximum likelihood method

Edisanter Lo

Proceedings Volume 9659, International Conference on Photonics Solutions 2015; 965914 (2015) https://doi.org/10.1117/12.2196550
Event: International Conference on Photonics Solutions 2015, 2015, Hua Hin, Thailand

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.

Citation Download Citation

Edisanter Lo "Hyperspectral anomaly detection based on maximum likelihood method", Proc. SPIE 9659, International Conference on Photonics Solutions 2015, 965914 (29 July 2015); https://doi.org/10.1117/12.2196550

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