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Image Noise Reduction by Means of Bootstrapping-Based Fuzzy Numbers

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Image Noise Reduction by Means of Bootstrapping-Based Fuzzy Numbers

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dc.contributor.author Ghasemi, Reza es_ES
dc.contributor.author Morillas, Samuel es_ES
dc.contributor.author Nezakati, Ahmad es_ES
dc.contributor.author Rabiei, Mohammadreza es_ES
dc.date.accessioned 2023-11-07T19:02:44Z
dc.date.available 2023-11-07T19:02:44Z
dc.date.issued 2022-10 es_ES
dc.identifier.uri http://hdl.handle.net/10251/199458
dc.description.abstract [EN] Removing or reducing noise in color images is one of the most important functions of image processing, which is used in many sciences. In many cases, nonlinear methods significantly reduce the noise in the image and are widely used today. One of these methods is the use of fuzzy logic. In this paper, we want to introduce a fuzzy filter by using the fuzzy metric for fuzzy sets. For this purpose, we define fuzzy color pixels by using the mean of neighborhoods. Due to the noise in the image, we use the bootstrap resampling method to reduce the effect of outliers. The concept of the strong law of large numbers for the bootstrap mean in fuzzy metric space helps us to use the resampling method. es_ES
dc.description.sponsorship Samuel Morillas acknowledges the support of the Generalitat Valenciana under Grant AICO2020-136. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Applied Sciences es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Fuzzy metric space es_ES
dc.subject Image processing es_ES
dc.subject Fuzzy filter es_ES
dc.subject Noise reduction es_ES
dc.subject Bootstrap resampling es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Image Noise Reduction by Means of Bootstrapping-Based Fuzzy Numbers es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/app12199445 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//AICO-2020-136/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Ghasemi, R.; Morillas, S.; Nezakati, A.; Rabiei, M. (2022). Image Noise Reduction by Means of Bootstrapping-Based Fuzzy Numbers. Applied Sciences. 12(19):1-14. https://doi.org/10.3390/app12199445 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/app12199445 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 14 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 19 es_ES
dc.identifier.eissn 2076-3417 es_ES
dc.relation.pasarela S\502217 es_ES
dc.contributor.funder Generalitat Valenciana es_ES


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