EPJ Web Conf.
Volume 238, 2020EOS Annual Meeting (EOSAM 2020)
|Number of page(s)||2|
|Section||Topical Meeting (TOM) 6- Frontiers in Optical Metrology|
|Published online||20 August 2020|
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: firstname.lastname@example.org
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
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