Denoising based on non local means for ultrasound images with simultaneous multiple noise distributions
dc.contributor.author | Salvadeo, Denis H. P. [UNESP] | |
dc.contributor.author | Bloch, Isabelle | |
dc.contributor.author | Tupin, Florence | |
dc.contributor.author | Mascarenhas, Nelson D. A. | |
dc.contributor.author | Levada, Alexandre L. M. | |
dc.contributor.author | Deledalle, Charles-Alban | |
dc.contributor.author | Dahdouh, Sonia | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.contributor.institution | Universidade Federal de São Carlos (UFSCar) | |
dc.contributor.institution | CNRS LTCI | |
dc.contributor.institution | Institut de Mathématiques de Bordeaux | |
dc.date.accessioned | 2022-04-29T07:26:35Z | |
dc.date.available | 2022-04-29T07:26:35Z | |
dc.date.issued | 2014-01-28 | |
dc.description.abstract | In 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.affiliation | São Paulo State University DEMAC | |
dc.description.affiliation | Federal University of São Carlos Computer Department | |
dc.description.affiliation | Institut Mines-Télécom Télécom ParisTech CNRS LTCI | |
dc.description.affiliation | Université Bordeaux 1 Institut de Mathématiques de Bordeaux | |
dc.description.affiliationUnesp | São Paulo State University DEMAC | |
dc.format.extent | 2699-2703 | |
dc.identifier | http://dx.doi.org/10.1109/ICIP.2014.7025546 | |
dc.identifier.citation | 2014 IEEE International Conference on Image Processing, ICIP 2014, p. 2699-2703. | |
dc.identifier.doi | 10.1109/ICIP.2014.7025546 | |
dc.identifier.scopus | 2-s2.0-84949929075 | |
dc.identifier.uri | http://hdl.handle.net/11449/228083 | |
dc.language.iso | eng | |
dc.relation.ispartof | 2014 IEEE International Conference on Image Processing, ICIP 2014 | |
dc.source | Scopus | |
dc.subject | image denoising | |
dc.subject | multiple noises | |
dc.subject | non local means | |
dc.subject | ultrasound image | |
dc.subject | ultrasound segmentation | |
dc.title | Denoising based on non local means for ultrasound images with simultaneous multiple noise distributions | en |
dc.type | Trabalho apresentado em evento | |
unesp.campus | Universidade Estadual Paulista (Unesp), Instituto de Geociências e Ciências Exatas, Rio Claro | pt |
unesp.department | Estatística, Matemática Aplicada e Computação - IGCE | pt |