Regularized Fourier Ptychography Using an Online Plug-and-play Algorithm

  • Yu Sun
  • , Shiqi Xu
  • , Yunzhe Li
  • , Lei Tian
  • , Brendt Wohlberg
  • , Ulugbek S. Kamilov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

56 Scopus citations

Abstract

The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser within an iterative algorithm. In this paper, we propose a new online PnP algorithm for Fourier ptychographic microscopy (FPM) based on the accelerated proximal gradient method (APGM). Specifically, the proposed algorithm uses only a subset of measurements, which makes it scalable to a large set of measurements. We validate the algorithm by showing that it can lead to significant performance gains on both simulated and experimental data.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7665-7669
Number of pages5
ISBN (Electronic)9781479981311
DOIs
StatePublished - May 2019
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: May 12 2019May 17 2019

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Country/TerritoryUnited Kingdom
CityBrighton
Period05/12/1905/17/19

Keywords

  • forward-backward algorithm
  • Fourier ptychography
  • nonconvex optimization
  • plug-and-play priors
  • proximal-gradient method
  • stochastic gradient descent

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