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Proceedings Paper

Compressive imaging measurement design from an image patch manifold prior
Author(s): Robert Muise; Dave Bottisti
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Paper Abstract

We look at the design of projective measurements based upon image priors. 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. Any sparse image reconstruction algorithm has improved performance using the developed measurement matrix over using random projections. Some insights into the empirical estimation of the image patch manifold are developed and several results are presented.

Paper Details

Date Published: 4 May 2012
PDF: 8 pages
Proc. SPIE 8399, Visual Information Processing XXI, 839905 (4 May 2012); doi: 10.1117/12.919659
Show Author Affiliations
Robert Muise, Lockheed Martin Missiles and Fire Control (United States)
Dave Bottisti, Lockheed Martin Missiles and Fire Control (United States)

Published in SPIE Proceedings Vol. 8399:
Visual Information Processing XXI
Mark Allen Neifeld; Amit Ashok, Editor(s)

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