Generic target response as a measure of regression accuracy in multispectral background estimation

This paper introduces a measure of regression fidelity that is directly linked to target detection performance in multispectral and hyperspectral imagery. The measure - called generic target response - maintains this link to target detection without specifying a particular target signature. It is compared to two other measures, one based on variance and one based on volume, in a regression framework that estimates local background from an annular neighborhood. The three generic measures are applied to two hyperspectral images, and are used to compare the performance of three different estimators (local mean, local median, and local linear fit), using two different rotations of the hyperspectral bands.

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