The reconstruction of spatially resolved information of an extended object from an observed intensity diffraction pattern in holographic imaging is a challenging problem. By incorporating an explicit physical model, Lee and colleagues propose a deep learning method that can be used in holographic image reconstruction under physical perturbations and which generalizes well beyond object-to-sensor distances and pixel sizes seen during training.
- Chanseok Lee
- Gookho Song
- Mooseok Jang
