Abstract
In this paper, a hybrid reflective hyperspectral target detection algorithm based on the Constrained Energy Minimization (CEM) and Kelly's detection algorithms is presented. Detection performance is evaluated using the dataset and scoring methodology of the Rochester Institute of Technology (RIT) Target Detection Blind Test project. Results show that the proposed hybrid algorithm enables the detection of subpixel targets at a false alarm rate lower than either CEM or Kelly's algorithms.
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