Stochastic Multigrid Method for Blind Ptychographic Phase Retrieval
By: Borong Zhang , Junjing Deng , Yi Jiang and more
Potential Business Impact:
Makes blurry images sharp and clear.
We present eMAGPIE (extended Multilevel-Adaptive-Guided Ptychographic Iterative Engine), a stochastic multigrid method for blind ptychographic phase retrieval that jointly recovers the object and the probe. We recast the task as the iterative minimization of a quadratic surrogate that majorizes the exit-wave misfit. From this surrogate, we derive closed-form updates, combined in a geometric-mean, phase-aligned joint step, yielding a simultaneous update of the object and probe with guaranteed descent of the sampled surrogate. This formulation naturally admits a multigrid acceleration that speeds up convergence. In experiments, eMAGPIE attains lower data misfit and phase error at comparable compute budgets and produces smoother, artifact-reduced phase reconstructions.
Similar Papers
MAGPIE: Multilevel-Adaptive-Guided Solver for Ptychographic Phase Retrieval
Numerical Analysis
Makes images clearer by solving a tricky puzzle.
A Message-Passing Perspective on Ptychographic Phase Retrieval
Applications
Improves picture-making from light patterns.
Fidelity-preserving enhancement of ptychography with foundational text-to-image models
Graphics
Cleans up blurry pictures using words.