20 May 2016 Scalable information-optimal compressive target recognition
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Proceedings Volume 9870, Computational Imaging; 987008 (2016); doi: 10.1117/12.2228570
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, Maryland, 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.
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Ronan Kerviche, Amit Ashok, "Scalable information-optimal compressive target recognition", Proc. SPIE 9870, Computational Imaging, 987008 (20 May 2016); doi: 10.1117/12.2228570; https://doi.org/10.1117/12.2228570
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KEYWORDS
Signal to noise ratio

Principal component analysis

Target recognition

Target recognition

Image compression

Imaging systems

Projection systems

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