From Event: SPIE Optical Engineering + Applications, 2017
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.
Lasith Adhikari, Reheman Baikejiang, Omar DeGuchy, and Roummel F. Marcia, "Non-convex Shannon entropy for photon-limited imaging," Proc. SPIE 10394, Wavelets and Sparsity XVII, 103940L (Presented at SPIE Optical Engineering + Applications: August 07, 2017; Published: 24 August 2017); https://doi.org/10.1117/12.2274466.
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