Open AccessHigh-accuracy phase demodulation method compatible to closed fringes in a single-frame interferogram based on deep learning
Author(s) -
Shizhu Yuan,
Yao Hu,
Qun Hao,
Shaohui Zhang
Publication year - 2021
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.413385
Subject(s) - demodulation , computer science , frame (networking) , interferometry , phase (matter) , optics , phase retrieval , artificial intelligence , root mean square , artificial neural network , fourier transform , physics , telecommunications , channel (broadcasting) , quantum mechanics
Interferogram demodulation is a fundamental problem in optical interferometry. It is still challenging to obtain high-accuracy phases from a single-frame interferogram that contains closed fringes. In this paper, we propose a neural network architecture for single-frame interferogram demodulation. Furthermore, instead of using real experimental data, an interferogram generation model is constructed to generate the dataset for the network's training. A four-stage training strategy adopting appropriate optimizers and loss functions is developed to guarantee the high-accuracy training of the network. The experimental results indicate that the proposed method can achieve a phase demodulation accuracy of 0.01 λ (root mean square error) for actual interferograms containing closed fringes.