Northeastern University
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Abstract: Remote Hyperspectral Imaging (HSI) is a powerful tool for identifying different materials on the surface of a large geographic area. Detection algorithms have been developed to detect specific target materials of interest in imaged scenes. Hyperspectral detection performance depends on the variability of the particular materials in a scene and the detection algorithm being used. Performance prediction of detection algorithms is important for understanding the capabilities and limitations of hyperspectral target detection. In this thesis, we present a robust and efficient technique...

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