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Proceedings Paper

Measurement kernel design for compressive imaging under device constraints
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Paper Abstract

We look at the design of projective measurements for compressive imaging based upon image priors and device constraints. If one assumes that image patches from natural imagery can be modeled as a low rank manifold, we develop an optimality criterion for a measurement matrix based upon separating the canonical elements of the manifold prior. We then describe a stochastic search algorithm for finding the optimal measurements under device constraints based upon a subspace mismatch algorithm. The algorithm is then tested on a prototype compressive imaging device designed to collect an 8x4 array of projective measurements simultaneously. This work is based upon work supported by DARPA and the SPAWAR System Center Pacific under Contract No. N66001-11-C-4092. The views expressed are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government.

Paper Details

Date Published: 31 May 2013
PDF: 12 pages
Proc. SPIE 8717, Compressive Sensing II, 871707 (31 May 2013); doi: 10.1117/12.2015441
Show Author Affiliations
Richard Shilling, Lockheed Martin Missiles and Fire Control (United States)
Robert Muise, Lockheed Martin Missiles and Fire Control (United States)


Published in SPIE Proceedings Vol. 8717:
Compressive Sensing II
Fauzia Ahmad, Editor(s)

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