Denoising based on non local means for ultrasound images with simultaneous multiple noise distributions

dc.contributor.authorSalvadeo, Denis H. P. [UNESP]
dc.contributor.authorBloch, Isabelle
dc.contributor.authorTupin, Florence
dc.contributor.authorMascarenhas, Nelson D. A.
dc.contributor.authorLevada, Alexandre L. M.
dc.contributor.authorDeledalle, Charles-Alban
dc.contributor.authorDahdouh, Sonia
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)
dc.contributor.institutionCNRS LTCI
dc.contributor.institutionInstitut de Mathématiques de Bordeaux
dc.date.accessioned2022-04-29T07:26:35Z
dc.date.available2022-04-29T07:26:35Z
dc.date.issued2014-01-28
dc.description.abstractIn this paper, an extension of the framework proposed by Deledalle et al. [1] for Non Local Means (NLM) method is proposed. This extension is a general adaptive method to denoise images containing multiple noises. It takes into account a segmentation stage that indicates the noise type of a given pixel in order to select the similarity measure and suitable parameters to perform the denoising task, considering a certain patch on the image. For instance, it has been experimentally observed that fetal 3D ultrasound images are corrupted by different types of noise, depending on the tissue. Finally, the proposed method is applied to denoise these images, showing very good results.en
dc.description.affiliationSão Paulo State University DEMAC
dc.description.affiliationFederal University of São Carlos Computer Department
dc.description.affiliationInstitut Mines-Télécom Télécom ParisTech CNRS LTCI
dc.description.affiliationUniversité Bordeaux 1 Institut de Mathématiques de Bordeaux
dc.description.affiliationUnespSão Paulo State University DEMAC
dc.format.extent2699-2703
dc.identifierhttp://dx.doi.org/10.1109/ICIP.2014.7025546
dc.identifier.citation2014 IEEE International Conference on Image Processing, ICIP 2014, p. 2699-2703.
dc.identifier.doi10.1109/ICIP.2014.7025546
dc.identifier.scopus2-s2.0-84949929075
dc.identifier.urihttp://hdl.handle.net/11449/228083
dc.language.isoeng
dc.relation.ispartof2014 IEEE International Conference on Image Processing, ICIP 2014
dc.sourceScopus
dc.subjectimage denoising
dc.subjectmultiple noises
dc.subjectnon local means
dc.subjectultrasound image
dc.subjectultrasound segmentation
dc.titleDenoising based on non local means for ultrasound images with simultaneous multiple noise distributionsen
dc.typeTrabalho apresentado em evento
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Geociências e Ciências Exatas, Rio Claropt
unesp.departmentEstatística, Matemática Aplicada e Computação - IGCEpt

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