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

Bradley Preece; Todd Du Bosq; Nader Namazi; Georges Nehmetallah; Kevin F. Kelly

doi:10.1117/12.2177275

12 May 2015 A noise model for the design of a compressive sensing imaging system

Bradley Preece, Todd Du Bosq, Nader Namazi, Georges Nehmetallah, Kevin F. Kelly

Proceedings Volume 9452, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI; 94520L (2015) https://doi.org/10.1117/12.2177275
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

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.

Citation Download Citation

Bradley Preece, Todd Du Bosq, Nader Namazi, Georges Nehmetallah, and Kevin F. Kelly "A noise model for the design of a compressive sensing imaging system", Proc. SPIE 9452, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI, 94520L (12 May 2015); https://doi.org/10.1117/12.2177275

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