arXiv · 1909.06482
Ptychographic phase-retrieval by proximal algorithms
Abstract
We derive a set of ptychography phase-retrieval iterative engines based on proximal algorithms originally developed in convex optimization theory, and discuss their connections with existing ones. The use of proximal operator creates a simple frame work that allows us to incorporate the effect of noise from a maximum-likelihood principle. We focus on three particular algorithms, namely proximal minimization, alternating direction method of multiplier and accelerated proximal gradient, and benckmark their performance with numerical simulations and experimental x-ray data. Among them, accelerated proximal gradient shows superior performance in terms of both accuracy and convergence rate for a noisy dataset.
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Hanfei Yan. 2019-09-13. Ptychographic phase-retrieval by proximal algorithms. https://doi.org/10.1088/1367-2630/ab704e
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