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Proceedings Paper

Automated target detection from compressive measurements
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Paper Abstract

A novel compressive imaging model is proposed that multiplexes segments of the field of view onto an infrared focal plane array (FPA). Similar to the compound eyes of insects, our imaging model is based on combining pixels from a surface comprising of different parts of the field of view (FOV). We formalize this superposition of pixels in a global multiplexing process reducing the resolution requirements of the FPA. We then apply automated target detection algorithms directed on the measurements of this model in a typical missile seeker scene. Based on quadratic correlation filters, we extend the target training and detection processes directly using these encoded measurements. Preliminary results are promising.

Paper Details

Date Published: 20 April 2016
PDF: 9 pages
Proc. SPIE 9845, Optical Pattern Recognition XXVII, 984502 (20 April 2016); doi: 10.1117/12.2222791
Show Author Affiliations
Richard Z. Shilling, Lockheed Martin Missiles and Fire Control (United States)
Robert R. Muise, Lockheed Martin Missiles and Fire Control (United States)

Published in SPIE Proceedings Vol. 9845:
Optical Pattern Recognition XXVII
David Casasent; Mohammad S. Alam, Editor(s)

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