9 January 2017 Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system
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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.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Daniel Gedalin, Daniel Gedalin, Yaniv Oiknine, Yaniv Oiknine, Isaac August, Isaac August, Dan G. Blumberg, Dan G. Blumberg, Stanley R. Rotman, Stanley R. Rotman, Adrian Stern, Adrian Stern, } "Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system," Optical Engineering 56(4), 041312 (9 January 2017). https://doi.org/10.1117/1.OE.56.4.041312 . Submission: Received: 11 October 2016; Accepted: 19 December 2016
Received: 11 October 2016; Accepted: 19 December 2016; Published: 9 January 2017
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