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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@inproceedings{feng2022adversarial,
  title={Adversarial Sensing for Sub-Diffraction Imaging},
  author={Feng, Brandon Y and Metzler, Christopher A},
  booktitle={Computational Optical Sensing and Imaging},
  pages={CF2C--3},
  year={2022},
  organization={Optica Publishing Group}
}