Adversarial Sensing for Sub-Diffraction Imaging

Brandon Y. Feng Christopher A. Metzler

Computational Optical Sensing and Imaging — 2022

[paper]

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We propose a self-supervised learning-based framework for reconstructing images from partially unknown and non-linear measurements. We apply our technique, which is based on matching the distributions of real and simulated observations, to long-range Fourier Ptychography.

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@article{ Feng2022Adversarial,
  author    = { Feng, Brandon Y. and Metzler, Christopher A. },
  title     = { Adversarial Sensing for Sub-Diffraction Imaging },
  journal   = { Computational Optical Sensing and Imaging },
  year      = { 2022 },
}