# Deep Ptych: Subsampled Fourier Ptychography using Generative Priors

## TL;DR

Deep Ptych introduces a generative prior-based method for Fourier ptychography, significantly enhancing reconstruction quality and noise robustness with fewer samples, and allowing exploration beyond the generative model's range.

## Contribution

The paper presents a novel deep learning framework that regularizes Fourier ptychography using generative models, improving reconstruction quality and robustness.

## Key findings

- Outperforms existing techniques in reconstruction quality
- Requires fewer samples for accurate results
- Enhances robustness against noise

## Abstract

This paper proposes a novel framework to regularize the highly ill-posed and non-linear Fourier ptychography problem using generative models. We demonstrate experimentally that our proposed algorithm, Deep Ptych, outperforms the existing Fourier ptychography techniques, in terms of quality of reconstruction and robustness against noise, using far fewer samples. We further modify the proposed approach to allow the generative model to explore solutions outside the range, leading to improved performance.