Directionally constrained or constrained energy minimization adaptive matched filter: theory and practice

Dimitris G. Manolakis; Gary A. Shaw

doi:10.1117/12.453327

17 January 2002 Directionally constrained or constrained energy minimization adaptive matched filter: theory and practice

Dimitris G. Manolakis, Gary A. Shaw

Author Affiliations +

Proceedings Volume 4480, Imaging Spectrometry VII; (2002) https://doi.org/10.1117/12.453327
Event: International Symposium on Optical Science and Technology, 2001, San Diego, CA, United States

Abstract

The constrained energy minimization (CEM) algorithm and the closely related matched filter processor have been widely used for target detection in hyperspectral data exploitation applications. In this paper, we look at the key assumptions underlying the derivation of each algorithm and the effect these assumptions have upon their performance. To illuminate and better understand their operation, we compare both algorithms to Fisher's linear discriminant and the quadratic Bayes classifier. Bayes classifier reduces to Fisher's linear discriminant when the target and background covariances are equal. Furthermore, Fisher's linear discriminant is reduced to the matched filter, when we look for low probability targets. These interrelations can be used to justify the use of the matched filter, which has been developed for the detection of known signals in additive noise, for hyperspectral target which are not corrupted by additive noise. Finally, we investigate under what conditions the output of the matched filter follows a normal distribution.

Citation Download Citation

Dimitris G. Manolakis and Gary A. Shaw "Directionally constrained or constrained energy minimization adaptive matched filter: theory and practice", Proc. SPIE 4480, Imaging Spectrometry VII, (17 January 2002); https://doi.org/10.1117/12.453327

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