https://doi.org/10.1051/epjconf/202023806009
Fringe Pattern Denoising using U-Net based neural network
1 Departamento de Fisica Aplicada. Universidade de Santiago de Compostela. Spain
2 RNASA-IMEDIR, Computer Science Faculty, University of A Coruna, 15071 A Coruña, Spain
3 CITIC, Computer Science Faculty, University of A Coruna, 15071 A Coruña, Spain
4 CITEEC, Computer Science Faculty, University of A Coruna, 15071 A Coruña, Spain
* Corresponding author: jose.crespo@me.com
Published online: 20 August 2020
Fringe visibility and noise removal, are key success factors in interferometric techniques, where novel deep learning techniques can be applied. We test the use U-Net deep convolutional network applied to the obtained interference images, trained with an ad-hoc generated image dataset with complex fringe patterns, computed using high order Zernike polynomials.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
