Abstract
A supervised subpixel target detection algorithm based on parametric general linear model using whitening transformation for hyperspectral imaging is developed. Statistical tests are described to assess the performance of the algorithm in comparison with the corresponding classical approach. Numerical results are presented to show that the parametric algorithm using low-order models can adequately represent the classical model.
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