Title
DEEP (SPR)-P-3: SIMULTANEOUS SOURCE SEPARATION AND PHASE RETRIEVAL USING DEEP GENERATIVE MODELS
Abstract
This paper introduces and solves the simultaneous source separation and phase retrieval ((SPR)-P-3) problem. (SPR)-P-3 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)-P-3 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)-P-3. 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.
Year
DOI
Venue
2021
10.1109/ICASSP39728.2021.9413714
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
Keywords
DocType
Citations 
Phase Retrieval, Source Separation, Deep Generative Models
Conference
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Metzler Christopher A.160.80
Gordon Wetzstein294572.47