Adaptive compressive imaging for object reconstruction

Jun Ke; Amit Ashok; Mark A. Neifeld

doi:10.1117/12.861738

27 August 2010 Adaptive compressive imaging for object reconstruction

Jun Ke, Amit Ashok, Mark A. Neifeld

Proceedings Volume 7818, Adaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems II; 781809 (2010) https://doi.org/10.1117/12.861738
Event: SPIE Optical Engineering + Applications, 2010, San Diego, California, United States

Abstract

Static Feature-specific imaging (SFSI) employing a fixed/static measurement basis has been shown to achieve superior reconstruction performance to conventional imaging under certain conditions.^1-5 In this paper, we describe an adaptive FSI system in which past measurements inform the choice of measurement basis for future measurements so as to maximize the reconstruction fidelity while employing the fewest measurements. An algorithm to implement an adaptive FSI system for principle component (PC) measurement basis is described. The resulting system is referred to as a PC-based adaptive FSI (AFSI) system. A simulation study employing the root mean squared error (RMSE) metric to quantify the reconstruction fidelity is used to analyze the performance of the PC-based AFSI system. We observe that the AFSI system achieves as much as 30% lower RMSE compared to a SFSI system.

Citation Download Citation

Jun Ke, Amit Ashok, and Mark A. Neifeld "Adaptive compressive imaging for object reconstruction", Proc. SPIE 7818, Adaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems II, 781809 (27 August 2010); https://doi.org/10.1117/12.861738

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