Deep S3PR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models

This paper introduces and solves the simultaneous source separation and phase retrieval (S³PR) problem. S³PR is an important but largely unsolved problem in a number application domains, including microscopy, wireless communication, and imaging through scattering media, where one has multiple independent coherent sources whose phase is difficult to measure. In general, S³PR is highly under-determined, non-convex, and difficult to solve. In this work, we demonstrate that by restricting the solutions to lie in the range of a deep generative model, we can constrain the search space sufficiently to solve S³PR.Code associated with this work is available at https://github.com/computational-imaging/DeepS3PR. An extended version of this work is available at https://arxiv.org/abs/2002.05856.