Special Section on Optical Computational Imaging

Performance assessment of a compressive sensing single-pixel imaging system

[+] Author Affiliations
Todd W. Du Bosq, Bradley L. Preece

U.S. Army Research, Development and Engineering Command, Communications-Electronics Research, Development and Engineering Center, Night Vision and Electronic Sensors Directorate, Fort Belvoir, Virginia, United States

Opt. Eng. 56(4), 041313 (Mar 07, 2017). doi:10.1117/1.OE.56.4.041313
History: Received September 23, 2016; Accepted February 10, 2017
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Abstract.  Conventional sensors measure the light incident at each pixel in a focal plane array. Compressive sensing (CS) involves capturing a smaller number of unconventional measurements from the scene, and then using a companion process to recover the image. CS has the potential to acquire imagery with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. However, the benefits of CS do not come without compromise. The CS architecture chosen must effectively balance between physical considerations, reconstruction accuracy, and reconstruction speed to meet operational requirements. Performance modeling of CS imagers is challenging due to the complexity and nonlinearity of the system and reconstruction algorithm. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts and sensitivity to noise. Imagery of a two-handheld object target set was collected using an shortwave infrared single-pixel CS camera for various ranges and number of processed measurements. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of CS modeling techniques are discussed.

© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Todd W. Du Bosq and Bradley L. Preece
"Performance assessment of a compressive sensing single-pixel imaging system", Opt. Eng. 56(4), 041313 (Mar 07, 2017). ; http://dx.doi.org/10.1117/1.OE.56.4.041313


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