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Scalable Information-optimal Compressive Imager: Target Recognition Task

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Abstract

We present a scalable compressive imager that employs information-optimal measurements capable of detecting and classifying two or more targets in natural backgrounds. Measurements are optimized using Cauchy-Schwarz mutual information that bounds the probability of error.

© 2016 Optical Society of America

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