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Proceedings Paper

Performance assessment of compressive sensing imaging
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Paper Abstract

Compressive sensing (CS) can potentially form an image of equivalent quality to a large format, megapixel array, using a smaller number of individual measurements. This has the potential to provide smaller, cheaper, and lower bandwidth imaging systems. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts, sensitivity to noise, and CS limitations. Full resolution imagery of an eight tracked vehicle target set at range was used as an input for simulated single-pixel CS camera measurements. The CS algorithm then reconstructs images from the simulated single-pixel CS camera for various levels of compression and noise. For comparison, a traditional camera was also simulated setting the number of pixels equal to the number of CS measurements in each case. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled with the Night Vision Integrated Performance Model (NVIPM) by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of compressive sensing modeling will be discussed.

Paper Details

Date Published: 29 May 2014
PDF: 12 pages
Proc. SPIE 9071, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXV, 90710G (29 May 2014); doi: 10.1117/12.2051435
Show Author Affiliations
Todd W. Du Bosq, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
David P. Haefner, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Bradley L. Preece, U.S. Army Night Vision & Electronic Sensors Directorate (United States)


Published in SPIE Proceedings Vol. 9071:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXV
Gerald C. Holst; Keith A. Krapels; Gary H. Ballard; James A. Buford; R. Lee Murrer, Editor(s)

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