Undersampled Phase Retrieval with Image Priors
Image and Video Processing
2025-09-19 v1 Machine Learning
Abstract
Phase retrieval seeks to recover a complex signal from amplitude-only measurements, a challenging nonlinear inverse problem. Current theory and algorithms often ignore signal priors. By contrast, we evaluate here a variety of image priors in the context of severe undersampling with structured random Fourier measurements. Our results show that those priors significantly improve reconstruction, allowing accurate reconstruction even below the weak recovery threshold.
Cite
@article{arxiv.2509.15026,
title = {Undersampled Phase Retrieval with Image Priors},
author = {Stanislas Ducotterd and Zhiyuan Hu and Michael Unser and Jonathan Dong},
journal= {arXiv preprint arXiv:2509.15026},
year = {2025}
}