Fringe pattern filtering using convolutional neural network

Ketao Yan; Jiaqi Shi; Tao Sun; Jiaxing Li; Yingjie Yu

doi:10.1117/12.2542401

16 October 2019 Fringe pattern filtering using convolutional neural network

Ketao Yan, Jiaqi Shi, Tao Sun, Jiaxing Li, Yingjie Yu

Proceedings Volume 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019); 112050O (2019) https://doi.org/10.1117/12.2542401
Event: Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 2019, Phuket, Thailand

Abstract

Fringe pattern denoising is an important process for fringe pattern analysis. In this paper, fringe pattern denoising using the convolutional neural network (CNN) is introduced. We use Gaussian functions to generate the various phase distributions, and then the required training samples are simulated according to theoretical formulas. The noisy fringe pattern can directly obtain the clean fringe pattern using the trained model. The denoising performance has been verified, which can recover high-quality fringe pattern.

Citation Download Citation

Ketao Yan, Jiaqi Shi, Tao Sun, Jiaxing Li, and Yingjie Yu "Fringe pattern filtering using convolutional neural network", Proc. SPIE 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 112050O (16 October 2019); https://doi.org/10.1117/12.2542401

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