Phase retrieval with a multivariate Von Mises prior: from a Bayesian formulation to a lifting solution

Angelique Dremeau; Antoine Deleforge

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arXiv · 1704.08972

Phase retrieval with a multivariate Von Mises prior: from a Bayesian formulation to a lifting solution

Angelique Dremeau·Antoine Deleforge

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Abstract

In this paper, we investigate a new method for phase recovery when prior information on the missing phases is available. In particular, we propose to take into account this information in a generic fashion by means of a multivariate Von Mises dis- tribution. Building on a Bayesian formulation (a Maximum A Posteriori estimation), we show that the problem can be expressed using a Mahalanobis distance and be solved by a lifting optimization procedure.

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Angelique Dremeau, Antoine Deleforge. 2017-04-28. Phase retrieval with a multivariate Von Mises prior: from a Bayesian formulation to a lifting solution. https://arxiv.org/abs/1704.08972

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