Deep distributed optimization for blind diffuser-modulation ptychography

Abstract

Blind diffuser-modulation ptychography has emerged as a low-cost technique for micro–nano holographic imaging, which enables breaking the resolution limit of optical systems. However, the existing reconstruction method requires thousands of measurements to recover object and diffuser profile simultaneously, which makes the data acquisition time-consuming and cumbersome. In this Letter, we report a novel, to the best of our knowledge, blind ptychography technique with deep distributed optimization, termed BPD2O. It decomposes the complicated optimization task into subproblems, then introduces extended ptychographical iterative engine and enhanced network solver to optimize each in a distributed strategy. In this way, BPD2O combines the advantages of both model-driven and data-driven strategies, realizing high-fidelity robust ptychography imaging. Extensive experiments validate that BPD2O can realize better resolution and lead to a reduction of more than one order of magnitude in the number of measurements.

Pixel Super-Resolution Phase Retrieval for Lensless On-Chip Microscopy via Accelerated Wirtinger Flow

“…As a result, to tackle the ill-posedness, we introduce another regularization term R(x) for the reconstruction problem. Apart from the total variation function adopted in this paper, the regularization function can take many other forms, such as BM3D [42,[61][62][63] and deep denoiser priors [64,65].…”

WASP: Weighted Average of Sequential Projections for ptychographic phase retrieval

“…Many more methods have been demonstrated at X-ray synchrotrons since this early work, including various set projection methods [13,14] (particularly Luke's Relaxed Averaged Alternating Reflections (RAAR) algorithm [15]), the Alternating Directions Method of Multipliers (ADMM) [16], proximal algorithms [17,18], and maximum likelihood [19]. Meanwhile, Fourier ptychography at optical wavelengths has brought new ideas [20][21][22], Machine Learning has appeared on the sceneeither as a source of optimisation algorithms and automatic differentiation routines [23,24] or as a direct solution method [25] -and in electron ptychography a flexible least-squares optimizer [26] was used recently to great effect to realise record-breaking picoscale resolutions [27].…”

WASP: Weighted Average of Sequential Projections for ptychographic phase retrieval

“…Many more methods have been demonstrated at X-ray synchrotrons since this early work, including various set projection methods [13,14] (particularly Luke's Relaxed Averaged Alternating Reflections (RAAR) algorithm [15]), the Alternating Directions Method of Multipliers (ADMM) [16], proximal algorithms [17,18], and maximum likelihood [19]. Meanwhile, Fourier ptychography at optical wavelengths has brought new ideas [20][21][22], Machine Learning has appeared on the sceneeither as a source of optimisation algorithms and automatic differentiation routines [23,24] or as a direct solution method [25] -and in electron ptychography a flexible least-squares optimizer [26] was used recently to great effect to realise record-breaking picoscale resolutions [27].…”