{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:10:26Z","timestamp":1760145026323,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,6,7]],"date-time":"2024-06-07T00:00:00Z","timestamp":1717718400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>The modeling of real objects digitally is an area that has generated a high demand due to the need to obtain systems that are able to reproduce 3D objects from real objects. To this end, several techniques have been proposed to model objects in a computer, with the fringe profilometry technique being the one that has been most researched. However, this technique has the disadvantage of generating Moire noise that ends up affecting the accuracy of the final 3D reconstructed object. In order to try to obtain 3D objects as close as possible to the original object, different techniques have been developed to attenuate the quasi\/periodic noise, namely the application of convolutional neural networks (CNNs), a method that has been recently applied for restoration and reduction and\/or elimination of noise in images applied as a pre-processing in the generation of 3D objects. For this purpose, this work is carried out to attenuate the quasi\/periodic noise in images acquired by the fringe profilometry technique, using a modified CNN-Multiresolution network. The results obtained are compared with the original CNN-Multiresolution network, the UNet network, and the FCN32s network and a quantitative comparison is made using the Image Mean Square Error E (IMMS), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Profile (MSE) metrics.<\/jats:p>","DOI":"10.3390\/computers13060145","type":"journal-article","created":{"date-parts":[[2024,6,7]],"date-time":"2024-06-07T08:05:17Z","timestamp":1717747517000},"page":"145","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Quasi\/Periodic Noise Reduction in Images Using Modified Multiresolution-Convolutional Neural Networks for 3D Object Reconstructions and Comparison with Other Convolutional Neural Network Models"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6730-2009","authenticated-orcid":false,"given":"Osmar Antonio","family":"Espinosa-Bernal","sequence":"first","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Quer\u00e9taro 76010, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5125-8907","authenticated-orcid":false,"given":"Jes\u00fas Carlos","family":"Pedraza-Ortega","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Quer\u00e9taro 76010, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5455-0329","authenticated-orcid":false,"given":"Marco Antonio","family":"Aceves-Fernandez","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Quer\u00e9taro 76010, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8006-1641","authenticated-orcid":false,"given":"Victor Manuel","family":"Mart\u00ednez-Su\u00e1rez","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Quer\u00e9taro 76010, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2695-1934","authenticated-orcid":false,"given":"Saul","family":"Tovar-Arriaga","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Quer\u00e9taro 76010, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2604-9692","authenticated-orcid":false,"given":"Juan Manuel","family":"Ramos-Arregu\u00edn","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Quer\u00e9taro 76010, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Efr\u00e9n","family":"Gorrostieta-Hurtado","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Quer\u00e9taro 76010, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,7]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Phase-shifting temporal phase unwrapping algorithm for high-speed fringe projection profilometry","volume":"72","author":"An","year":"2023","journal-title":"IEEE Trans. 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