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Proceedings Paper

A noise model for the design of a compressive sensing imaging system
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Paper Abstract

The design and modeling of compressive sensing (CS) imagers is difficult due to the complexity and non-linearity of the system and reconstruction algorithm. The Night Vision Integrated Performance Model (NV-IPM) is a linear imaging system design tool that is very useful for complex system trade studies. The custom component generator, included in NV-IPM, will be used to include a recently published theory for CS that links measurement noise, easily calculated with NV-IPM, to the noise of the reconstructed CS image given the estimated sparsity of the scene and the number of measurements as input. As the sparsity will also depend on other factors such as the optical transfer function and the scene content, an empirical relationship will be developed between the linear model within NV-IPM and the non-linear reconstruction algorithm using measured test data. Using the theory, a CS imager varying the number of measurements will be compared to a notional traditional imager.

Paper Details

Date Published: 12 May 2015
PDF: 11 pages
Proc. SPIE 9452, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI, 94520L (12 May 2015); doi: 10.1117/12.2177275
Show Author Affiliations
Bradley Preece, U.S. Army Night Vision and Electronic Sensors Directorate (United States)
Todd Du Bosq, U.S. Army Night Vision and Electronic Sensors Directorate (United States)
Nader Namazi, The Catholic Univ. of America (United States)
Georges Nehmetallah, The Catholic Univ. of America (United States)
Kevin F. Kelly, Rice Univ. (United States)


Published in SPIE Proceedings Vol. 9452:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI
Gerald C. Holst; Keith A. Krapels, Editor(s)

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