Compressed Sensing-Based Robust Phase Retrieval via Deep Generative Priors
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2020.3018751
Abstract: Algorithmic phase retrieval offers an alternative means to recover the phase of optical images without requiring sophisticated measurement setups such as holography. This article proposes a framework to regularize the highly ill-posed and non-linear phase… read more here.
Keywords: generative priors; phase retrieval; deep generative; proposed approach ... See more keywords
Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2023.3236155
Abstract: Most modern imaging systems incorporate a computational pipeline to infer the image of interest from acquired measurements. The Bayesian approach to solve such ill-posed inverse problems involves the characterization of the posterior distribution of the… read more here.
Keywords: generative priors; bayesian inversion; imaging models; deep generative ... See more keywords