Accelerated Wirtinger Flow: A fast algorithm for ptychography
arXiv:1806.05546
Abstract
This paper presents a new algorithm, Accelerated Wirtinger Flow (AWF), for ptychographic image reconstruction from phaseless diffraction pattern measurements. AWF is based on combining Nesterov's acceleration approach with Wirtinger gradient descent. Theoretical results enable prespecification of all AWF algorithm parameters, with no need for computationally-expensive line searches and no need for manual parameter tuning. AWF is evaluated in the context of simulated X-ray ptychography, where we demonstrate fast convergence and low per-iteration computational complexity. We also show examples where AWF reaches higher image quality with less computation than classical algorithms. AWF is also shown to have robustness to noise and probe misalignment.
References in corpus (6)
- Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation
- Solving (most) of a set of quadratic equalities: Composite optimization for robust phase retrieval
- Phase Retrieval via Polytope Optimization: Geometry, Phase Transitions, and New Algorithms
- Convergence of the randomized Kaczmarz method for phase retrieval
- Convolutional Phase Retrieval via Gradient Descent
- Optimization-based AMP for Phase Retrieval: The Impact of Initialization and -regularization
Cited by in corpus (5)
- PtyLab.m/py/jl: a cross-platform, open-source inverse modeling toolbox for conventional and Fourier ptychography
- Ptychographic phase-retrieval by proximal algorithms
- Inverse Multislice Ptychography by Layer-wise Optimisation and Sparse Matrix Decomposition
- PtychoDV: Vision Transformer-Based Deep Unrolling Network for Ptychographic Image Reconstruction
- A matrix-free Levenberg-Marquardt algorithm for efficient ptychographic phase retrieval