Phase unwrapping with the convolutional neural network

Shuai Wang; Bo Chen; Jing Wang

doi:10.1117/12.2575485

10 October 2020 Phase unwrapping with the convolutional neural network

Shuai Wang, Bo Chen, Jing Wang

Proceedings Volume 11551, Holography, Diffractive Optics, and Applications X; 115511U (2020) https://doi.org/10.1117/12.2575485
Event: SPIE/COS Photonics Asia, 2020, Online Only

Conference Poster

Abstract

Phase unwrapping is a classical signal processing problem, which refers to the recovery of the original phase value from the wrapped phase. Two dimensional phase unwrapping is widely used in optical measurement technology, such as digital holographic interferometry, fringe projection profilometry, synthetic aperture radar and many other applications. In this paper, a phase unwrapping method with the convolution neural network is proposed, and the feasibility is analyzed by numerical simulation. The convolution neural networks with different parameters are set up, and the phase screens used for the training set and testing set of convolution neural network are simulated with MATLAB software. The numerical simulation results show that the four convolution neural network models can be used for phase unwrapping, but the parameters have a significant impact on its accuracy.

Citation Download Citation

Shuai Wang, Bo Chen, and Jing Wang "Phase unwrapping with the convolutional neural network", Proc. SPIE 11551, Holography, Diffractive Optics, and Applications X, 115511U (10 October 2020); https://doi.org/10.1117/12.2575485

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