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Optical Engineering

Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system
Author(s): Daniel Gedalin; Yaniv Oiknine; Isaac August; Dan G. Blumberg; Stanley R. Rotman; Adrian Stern
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Paper Abstract

Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed hyperspectral cubes. We evaluate the utility of the data captured using the CS-MUSI system for the task of target detection. Specifically, we compare the performance of the matched filter target detection algorithm in traditional hyperspectral systems and in CS-MUSI multiplexed hyperspectral cubes. We found that the target detection algorithm performs similarly in both cases, despite the fact that the CS-MUSI data is up to an order of magnitude less than that in conventional hyperspectral cubes. Moreover, the target detection is approximately an order of magnitude faster in CS-MUSI data.

Paper Details

Date Published: 9 January 2017
PDF: 6 pages
Opt. Eng. 56(4) 041312 doi: 10.1117/1.OE.56.4.041312
Published in: Optical Engineering Volume 56, Issue 4
Show Author Affiliations
Daniel Gedalin, Ben-Gurion Univ. of the Negev (Israel)
Yaniv Oiknine, Ben-Gurion Univ. of the Negev (Israel)
Isaac August, Ben-Gurion Univ. of the Negev (Israel)
Dan G. Blumberg, Ben-Gurion Univ. of the Negev (Israel)
Stanley R. Rotman, Ben-Gurion Univ. of the Negev (Israel)
Adrian Stern, Ben-Gurion Univ. of the Negev (Israel)


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