Deep S$^3$PR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models
Machine Learning
2020-10-15 v2 Image and Video Processing
Machine Learning
Abstract
This paper introduces and solves the simultaneous source separation and phase retrieval (SPR) problem. SPR 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, SPR 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 SPR.
Cite
@article{arxiv.2002.05856,
title = {Deep S$^3$PR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models},
author = {Christopher A. Metzler and Gordon Wetzstein},
journal= {arXiv preprint arXiv:2002.05856},
year = {2020}
}