Anomaly and target detection by means of nonparametric density estimation

G. A. Tidhar; S. R. Rotman

doi:10.1117/12.919638

24 May 2012 Anomaly and target detection by means of nonparametric density estimation

G. A. Tidhar, S. R. Rotman

Proceedings Volume 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII; 839020 (2012) https://doi.org/10.1117/12.919638
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

We describe a novel completely non parametric high-dimension joint density estimation algorithm suited for anomaly and target detection using hyperspectral imaging. The new algorithm is compared against linear matched filter detection schemes with different available sample sizes, background statistics (MVN, GMM and non Gaussian). The new algorithm is shown to be superior in important cases.

Citation Download Citation

G. A. Tidhar and S. R. Rotman "Anomaly and target detection by means of nonparametric density estimation", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839020 (24 May 2012); https://doi.org/10.1117/12.919638

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