Fast and robust phase retrieval for masked coherent diffractive imaging

Abstract

Conventional phase retrieval algorithms for coherent diffractive imaging (CDI) require many iterations to deliver reasonable results, even using a known mask as a strong constraint in the imaging setup, an approach known as masked CDI. This paper proposes a fast and robust phase retrieval method for masked CDI based on the alternating direction method of multipliers (ADMM). We propose a plug-and-play ADMM to incorporate the prior knowledge of the mask, but note that commonly used denoisers are not suitable as regularizers for complex-valued latent images directly. Therefore, we develop a regularizer based on the structure tensor and Harris corner detector. Compared with conventional phase retrieval methods, our technique can achieve comparable reconstruction results with less time for the masked CDI. Moreover, validation experiments on real in situ CDI data for both intensity and phase objects show that our approach is more than 100 times faster than the baseline method to reconstruct one complex-valued image, making it possible to be used in challenging situations, such as imaging dynamic objects. Furthermore, phase retrieval results for single diffraction patterns show the robustness of the proposed ADMM.