Phase-Retrieval as a Regularization Problem
Numerical Analysis
2017-02-20 v1
Abstract
It was recently shown that the phase retrieval imaging of a sample can be modeled as a simple convolution process. Sometimes, such a convolution depends on physical parameters of the sample which are difficult to estimate a priori. In this case, a blind choice for those parameters usually lead to wrong results, e.g., in posterior image segmentation processing. In this manuscript, we propose a simple connection between phase-retrieval algorithms and optimization strategies, which lead us to ways of numerically determining the physical parameters
Cite
@article{arxiv.1702.05092,
title = {Phase-Retrieval as a Regularization Problem},
author = {Eduardo X. Miqueles and Nathaly L. Archilha and Marcelo R. Dos Anjos and Harry Westfahl and Elias S. Helou},
journal= {arXiv preprint arXiv:1702.05092},
year = {2017}
}