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Proceedings Paper

Experimental study of super-resolution using a compressive sensing architecture
Author(s): J. Christopher Flake; Gary Euliss; John B. Greer; Stephanie Shubert; Glenn Easley; Kevin Gemp; Brian Baptista; Michael D. Stenner; Phil A. Sallee
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Paper Abstract

An experimental investigation of super-resolution imaging from measurements of projections onto a random basis is presented. In particular, a laboratory imaging system was constructed following an architecture that has become familiar from the theory of compressive sensing. The system uses a digital micromirror array located at an intermediate image plane to introduce binary matrices that represent members of a basis set. The system model was developed from experimentally acquired calibration data which characterizes the system output corresponding to each individual mirror in the array. Images are reconstructed at a resolution limited by that of the micromirror array using the split Bregman approach to total-variation regularized optimization. System performance is evaluated qualitatively as a function of the size of the basis set, or equivalently, the number of snapshots applied in the reconstruction.

Paper Details

Date Published: 23 May 2014
PDF: 9 pages
Proc. SPIE 9109, Compressive Sensing III, 91090F (23 May 2014); doi: 10.1117/12.2050887
Show Author Affiliations
J. Christopher Flake, The MITRE Corp. (United States)
Booz Allen Hamilton Inc. (United States)
Gary Euliss, The MITRE Corp. (United States)
John B. Greer, National Geospatial-Intelligence Agency (United States)
Stephanie Shubert, National Geospatial-Intelligence Agency (United States)
Glenn Easley, The MITRE Corp. (United States)
Kevin Gemp, The MITRE Corp. (United States)
Brian Baptista, National Geospatial-Intelligence Agency (United States)
Michael D. Stenner, The MITRE Corp. (United States)
Phil A. Sallee, Booz Allen Hamilton Inc. (United States)

Published in SPIE Proceedings Vol. 9109:
Compressive Sensing III
Fauzia Ahmad, Editor(s)

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