2007 IEEE International Conference on Image Processing - San Antonio, Texas, U.S.A. - September 16-19, 2007

Technical Program

Paper Detail

Paper:TP-L4.3
Session:Geosciences and Remote Sensing I
Time:Tuesday, September 18, 15:10 - 15:30
Presentation: Lecture
Title: REGULARIZED SPECTRAL MATCHED FILTER FOR TARGET DETECTION IN HYPERSPECTRAL IMAGERY
Authors: Nasser Nasrabadi; US Army Research Laboratory 
Abstract: This paper describes a new adaptive spectral matched filter that incorporates the idea of regularization (shrinkage) to penalize and shrink the filter coefficients to a range of values. The regularization has the effect of restricting the possible matched filters (models) to a subset which are more stable and have better performance than the non-regularized adaptive spectral matched filters. The effect of regularization depends on the form of the regularization term and the amount of regularization is controlled by so called the regularization coefficient. Experimental results for detecting targets in hyperspectral imagery are presented for regularized and non-regularized spectral matched filters.



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