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Application of integrated sensing and processing decision trees for target detection and localization on digital mirror array imagery

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Abstract

We demonstrate the applicability of integrated sensing and processing decision trees (ISPDTs) methodology to a set of digital mirror array (DMA) hyperspectral imagery. In particular, we demonstrate that ISPDTs can be used to detect and localize targets by using just a few DMA Hadamard frames, so that an entire hyperspectral data cube need not be collected to successfully perform the given task. This suggests that such an integrated sensing–processing suite may be appropriate for extremely time-sensitive pattern-recognition applications.

© 2006 Optical Society of America

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