Measurement kernel design for compressive imaging under device constraints

Richard Shilling; Robert Muise

doi:10.1117/12.2015441

31 May 2013 Measurement kernel design for compressive imaging under device constraints

Richard Shilling, Robert Muise

Proceedings Volume 8717, Compressive Sensing II; 871707 (2013) https://doi.org/10.1117/12.2015441
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

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.

Citation Download Citation

Richard Shilling and Robert Muise "Measurement kernel design for compressive imaging under device constraints", Proc. SPIE 8717, Compressive Sensing II, 871707 (31 May 2013); https://doi.org/10.1117/12.2015441

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