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20 April 2016 Automated target detection from compressive measurements
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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.
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Richard Z. Shilling and Robert R. Muise "Automated target detection from compressive measurements", Proc. SPIE 9845, Optical Pattern Recognition XXVII, 984502 (20 April 2016);

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