A Flexible Phase Retrieval Framework for Flux-limited Coherent X-Ray Imaging

Abstract

Coherent X-ray diffraction imaging (CXDI) experiments are intrinsically limited by shot noise, a lack of prior knowledge about the sample's support, and missing measurements due to the experimental geometry. We propose a flexible, iterative phase retrieval framework that allows for accurate modeling of Gaussian or Poissonian noise statistics, modified support updates, regularization of reconstructed signals, and handling of missing data in the observations. The proposed method is efficiently solved using alternating direction method of multipliers (ADMM) and is demonstrated to consistently outperform state-of-the-art algorithms for low-photon phase retrieval from CXDI experiments, both for simulated diffraction patterns and for experimental measurements.