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Proceedings Paper

Recent results of integrated sensing and processing using a programmable hyperspectral imaging sensor
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Paper Abstract

In this paper we present an information sensing system which integrates sensing and processing resulting in the direct collection of data which is relevant to the application. Broadly, integrated sensing and processing (ISP) considers algorithms that are integrated with the collection of data. That is, traditional sensor development tries to come up with the "best" sensor in terms of SNR, resolution, data rates, integration time, etc. and traditional algorithm development tasks might wish to optimize probability of detection, false alarm rate, class separability, etc. For a typical Automatic Target Recognition (ATR) problem, the goal of ISP is to field algorithms which "tell" the sensor what kind of data to collect next and the sensor alters its parameters to collect the "best" information in order that the algorithm performs optimally. We demonstrate an ISP system which utilizes a near Infrared (NIR) Hadamard multiplexing imaging sensor. This prototype sensor incorporates a digital mirror array (DMA) device in order to realize a Hadamard multiplexed imaging system. Specific Hadamard codes can be sent to the sensor to realize inner products of the underlying scene rather than the scene itself. The developed ISP algorithm uses an ATR metric to send codes to the sensor in order to collect only the information relevant to the ATR problem. The result is a multiple resolution hyperspectral cube with full resolution where targets are present and less than full resolution where there are no targets. Essentially, this is compressed sensing.

Paper Details

Date Published: 17 April 2006
PDF: 15 pages
Proc. SPIE 6245, Optical Pattern Recognition XVII, 624502 (17 April 2006); doi: 10.1117/12.673440
Show Author Affiliations
Robert Muise, Lockheed Martin, MFC (United States)
Abhijit Mahalanobis, Lockheed Martin, MFC (United States)


Published in SPIE Proceedings Vol. 6245:
Optical Pattern Recognition XVII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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