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dc.contributor | 31249 | es_ES |
dc.contributor | 20608 | |
dc.contributor.other | https://orcid.org/0000-0002-7337-8974 | |
dc.coverage.spatial | Global | es_ES |
dc.creator | Villa Hernández, José de Jesús | |
dc.creator | González Ramírez, Efrén | |
dc.creator | Moreon, Gamaliel | |
dc.creator | De la Rosa Vargas, José Ismael | |
dc.creator | Flores, Jorge Luís | |
dc.creator | Alaniz Lumbreras, Daniel | |
dc.date.accessioned | 2020-04-17T19:58:08Z | |
dc.date.available | 2020-04-17T19:58:08Z | |
dc.date.issued | 2020-02 | |
dc.identifier | info:eu-repo/semantics/publishedVersion | es_ES |
dc.identifier.issn | 0030-4018 | es_ES |
dc.identifier.uri | http://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1726 | |
dc.identifier.uri | https://doi.org/10.48779/6rxw-g822 | |
dc.description.abstract | In this paper, it is proposed a gaussian convolution-based fringe pattern denoising method. As will be shown, this method is robust enough compared with some of the most outstanding methods in the literature. Additionally, the proposed method overcomes the problem of underperformance in low-frequency fringes that is common in most oriented filtering methods, while keeping the great advantages of convolution-based filters. The advantages of the proposed denoising method will be demonstrated with experiments realized over synthetic and real fringe patterns, and comparing the performance with four representative methods, already reported. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | https://doi.org/10.1016/j.optcom.2019.124704 | es_ES |
dc.relation.uri | generalPublic | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.source | Optics Communications, Vol. 457, febrero de 2020, pp. 124704 | es_ES |
dc.subject.classification | INGENIERIA Y TECNOLOGIA [7] | es_ES |
dc.subject.other | Fringe images | es_ES |
dc.subject.other | Filtering | es_ES |
dc.subject.other | Gaussian filters | es_ES |
dc.title | Fringe pattern denoising using spatial oriented gaussian filters | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
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