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Proceedings Paper

Non-convex Shannon entropy for photon-limited imaging
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Paper Abstract

Reconstructing high-dimensional sparse signals from low-dimensional low-count photon observations is a challenging nonlinear optimization problem. In this paper, we build upon previous work on minimizing the Poisson log-likelihood and incorporate recent work on the generalized nonconvex Shannon entropy function for promoting sparsity in solutions. We explore the effectiveness of the proposed approach using numerical experiments.

Paper Details

Date Published: 24 August 2017
PDF: 7 pages
Proc. SPIE 10394, Wavelets and Sparsity XVII, 103940L (24 August 2017); doi: 10.1117/12.2274466
Show Author Affiliations
Lasith Adhikari, Univ. of Florida (United States)
Reheman Baikejiang, Univ. of California, Merced (United States)
Omar DeGuchy, Univ. of California, Merced (United States)
Roummel F. Marcia, Univ. of California, Merced (United States)


Published in SPIE Proceedings Vol. 10394:
Wavelets and Sparsity XVII
Yue M. Lu; Dimitri Van De Ville; Manos Papadakis, Editor(s)

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