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Harnessing Sparsity over the Continuum: Atomic Norm Minimization for Super Resolution

04/08/2019

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by Yuejie Chi, et al.

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Convex optimization recently emerges as a compelling framework for performing super resolution, garnering significant attention from multiple communities spanning signal processing, applied mathematics, and optimization. This article offers a friendly exposition to atomic norm minimization as a canonical convex approach to solve super resolution problems. The mathematical foundations and performances guarantees of this approach are presented, and its application in super resolution image reconstruction for single-molecule fluorescence microscopy are highlighted.

Yuejie Chi
64 publications
Maxime Ferreira Da Costa
7 publications

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