Plug-and-Play Half-Quadratic Splitting for Ptychography
This work addresses noise and computational challenges in ptychography, a domain-specific imaging technique, but appears incremental as it adapts existing plug-and-play methods to this context.
The authors tackled the computational intensity and noise sensitivity in ptychographic image reconstruction by proposing a half-quadratic splitting framework that integrates plug-and-play and other data-driven priors, achieving validated effectiveness on natural and real test objects.
Ptychography is a coherent diffraction imaging method that uses phase retrieval techniques to reconstruct complex-valued images. It achieves this by sequentially illuminating overlapping regions of a sample with a coherent beam and recording the diffraction pattern. Although this addresses traditional imaging system challenges, it is computationally intensive and highly sensitive to noise, especially with reduced illumination overlap. Data-driven regularisation techniques have been applied in phase retrieval to improve reconstruction quality. In particular, plug-and-play (PnP) offers flexibility by integrating data-driven denoisers as implicit priors. In this work, we propose a half-quadratic splitting framework for using PnP and other data-driven priors for ptychography. We evaluate our method both on natural images and real test objects to validate its effectiveness for ptychographic image reconstruction.