Scalable information-optimal compressive target recognition

Ronan Kerviche; Amit Ashok

doi:10.1117/12.2228570

20 May 2016 Scalable information-optimal compressive target recognition

Ronan Kerviche, Amit Ashok

Proceedings Volume 9870, Computational Imaging; 987008 (2016) https://doi.org/10.1117/12.2228570
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States

Abstract

We present a scalable information-optimal compressive imager optimized for the target classification task, discriminating between two target classes. Compressive projections are optimized using the Cauchy-Schwarz Mutual Information (CSMI) metric, which provides an upper-bound to the probability of error of target classification. The optimized measurements provide significant performance improvement relative to random and PCA secant projections. We validate the simulation performance of information-optimal compressive measurements with experimental data.

Citation Download Citation

Ronan Kerviche and Amit Ashok "Scalable information-optimal compressive target recognition", Proc. SPIE 9870, Computational Imaging, 987008 (20 May 2016); https://doi.org/10.1117/12.2228570

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