Performance assessment of compressive sensing imaging

Todd W. Du Bosq; David P. Haefner; Bradley L. Preece

doi:10.1117/12.2051435

29 May 2014 Performance assessment of compressive sensing imaging

Todd W. Du Bosq, David P. Haefner, Bradley L. Preece

Proceedings Volume 9071, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXV; 90710G (2014) https://doi.org/10.1117/12.2051435
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

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.

Citation Download Citation

Todd W. Du Bosq, David P. Haefner, and Bradley L. Preece "Performance assessment of compressive sensing imaging", Proc. SPIE 9071, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXV, 90710G (29 May 2014); https://doi.org/10.1117/12.2051435

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