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Application of smooth fuzzy model in image denoising and edge detection

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Inteligencia Artificial Aplicada (GIAA)es
dc.contributor.authorSadjadi, Ebrahim
dc.contributor.authorSadrian Zadeh, Danial
dc.contributor.authorMoshiri, Behzad
dc.contributor.authorGarcía Herrero, Jesús
dc.contributor.authorMolina López, José Manuel
dc.contributor.authorFernández, Roemi
dc.contributor.funderComunidad de Madrides
dc.contributor.funderMinisterio de Ciencia e Innovación (España)es
dc.date.accessioned2023-04-12T08:16:07Z
dc.date.available2023-04-12T08:16:07Z
dc.date.issued2022-07-02
dc.descriptionThis article belongs to the Special Issue Soft Methods for Modeling Uncertainty and Imprecision.en
dc.description.abstractIn this paper, the bounded variation property of fuzzy models with smooth compositions have been studied, and they have been compared with the standard fuzzy composition (e.g., min-max). Moreover, the contribution of the bounded variation of the smooth fuzzy model for the noise removal and edge preservation of the digital images has been investigated. Different simulations on the test images have been employed to verify the results. The performance index related to the detected edges of the smooth fuzzy models in the presence of both Gaussian and Impulse (also known as salt-and-pepper noise) noises of different densities has been found to be higher than the standard well-known fuzzy models (e.g., min-max composition), which demonstrates the efficiency of smooth compositions in comparison to the standard composition.en
dc.description.sponsorshipThis research was partially funded by public research projects of Spanish Ministry of Science and Innovation, references PID2020-118249RB-C22 and PDC2021-121567-C22-AEI/10.13039/501100011033, and by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors, reference EPUC3M17.en
dc.format.extent25
dc.identifier.bibliographicCitationSadjadi, E. N., Sadrian Zadeh, D., Moshiri, B., García Herrero, J., Molina López, J. M., & Fernández, R. (2022). Application of Smooth Fuzzy Model in Image Denoising and Edge Detection. Mathematics, 10(14), 2421.en
dc.identifier.doihttps://doi.org/10.3390/math10142421
dc.identifier.issn2227-7390
dc.identifier.publicationfirstpage1
dc.identifier.publicationissue14, 2421
dc.identifier.publicationlastpage25
dc.identifier.publicationtitleMathematicsen
dc.identifier.publicationvolume10
dc.identifier.urihttps://hdl.handle.net/10016/37033
dc.identifier.uxxiAR/0000031392
dc.language.isoeng
dc.publisherMDPI
dc.relation.projectIDGobierno de España. PID2020-118249RB-C22es
dc.relation.projectIDGobierno de España. PDC2021-121567-C22es
dc.relation.projectIDComunidad de Madrid. EPUC3M17es
dc.rights© 2022 by the authors.en
dc.rightsAtribución 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subject.ecienciaElectrónicaes
dc.subject.ecienciaInformáticaes
dc.subject.ecienciaRobótica e Informática Industriales
dc.subject.otherBounded variation functionen
dc.subject.otherEdge detectionen
dc.subject.otherFuzzy modelsen
dc.subject.otherNoise reductionen
dc.subject.otherSmooth compositionsen
dc.titleApplication of smooth fuzzy model in image denoising and edge detectionen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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