A two-stage neural network recovering phase from a single-frame phase-shifted hologram

Tianhe Wang; Lin Liu; Jiaxi Zhao; Jing Zhang; Juanxiu Liu; Xiaohui Du; Ruqian Hao; Yi Liu

doi:10.1117/12.3007260

13 December 2023 A two-stage neural network recovering phase from a single-frame phase-shifted hologram

Tianhe Wang, Lin Liu, Jiaxi Zhao, Jing Zhang, Juanxiu Liu, Xiaohui Du, Ruqian Hao, Yi Liu

Proceedings Volume 12942, First Advanced Imaging and Information Processing Conference (AIIP 2023); 129420G (2023) https://doi.org/10.1117/12.3007260
Event: 1st Advanced Imaging and Information Processing, 2023, Jinggangshan, China

Abstract

Quantitative phase imaging and measurement of surface topography and fluid dynamics for objects, especially for moving objects, is critical in various fields. Phase-shifting digital holography, as a highly accurate phase measurement technology applied for moving objects, is limited by some aspects, such as dynamic phase measurement, accuracy of phase shift and temporal phase sensitivity. In this study, we proposed a two-stage neural network (VY-Net) for one shot phase recovery. This Y-Net generates two holograms with specific phase shifts from a single-frame phase shifted hologram, then V-Net recovering the phase with the three holograms input. Simulation results prove that the proposed method can provide an alternative approach for systems of phase-shifting digital holography based on common-path configuration to realize rapid phase-shifted holograms acquisition and accurate phase measurement.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tianhe Wang, Lin Liu, Jiaxi Zhao, Jing Zhang, Juanxiu Liu, Xiaohui Du, Ruqian Hao, and Yi Liu "A two-stage neural network recovering phase from a single-frame phase-shifted hologram", Proc. SPIE 12942, First Advanced Imaging and Information Processing Conference (AIIP 2023), 129420G (13 December 2023); https://doi.org/10.1117/12.3007260

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KEYWORDS

Holograms

Phase shifts

Convolution

Education and training

Digital holography

Phase recovery

Phase measurement

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