Phase retrieval with physics informed zero-shot network.

@article{Kumar2021PhaseRW,
  title={Phase retrieval with physics informed zero-shot network.},
  author={Sanjeev Kumar},
  journal={Optics letters},
  year={2021},
  volume={46 23},
  pages={
          5942-5945
        }
}
Phase can be reliably estimated from a single diffracted intensity image if faithful prior information about the object is available. Examples include amplitude bounds, object support, sparsity in the spatial or transform domain, deep image prior, and the prior learned from labeled datasets by a deep neural network. Deep learning facilitates state-of-the-art reconstruction quality but requires a large labeled dataset (ground truth measurement pair acquired in the same experimental conditions… 

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