Regularized Fourier Ptychography using an Online Plug-and-Play Algorithm
This work addresses scalability issues in microscopy imaging, but it is incremental as it adapts existing plug-and-play methods to a specific domain.
The paper tackled the problem of scalable image reconstruction in Fourier ptychographic microscopy by proposing an online plug-and-play algorithm based on FISTA, which uses subsets of measurements and achieved significant performance gains on simulated and experimental data.
The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser within an iterative algorithm. In this paper, we propose a new online PnP algorithm for Fourier ptychographic microscopy (FPM) based on the fast iterative shrinkage/threshold algorithm (FISTA). Specifically, the proposed algorithm uses only a subset of measurements, which makes it scalable to a large set of measurements. We validate the algorithm by showing that it can lead to significant performance gains on both simulated and experimental data.