Publication: Content-aware image smoothing based on fuzzy clustering
Date
2022
Authors
Mir Fuentes, Arnau
Mendióroz Iriarte, Maite
Baets, Bernard de
Director
Publisher
Springer
Acceso abierto / Sarbide irekia
Contribución a congreso / Biltzarrerako ekarpena
Versión aceptada / Onetsi den bertsioa
Project identifier
European Commission/Horizon 2020 Framework Programme/801586
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/
Abstract
Literature contains a large variety of content-aware smoothing methods. As opposed to classical smoothing methods, content-aware ones intend to regularize the image while avoiding the loss of relevant visual information. In this work, we propose a novel approach to contentaware image smoothing based on fuzzy clustering, specifically the Spatial Fuzzy c-Means (SFCM) algorithm. We develop the proposal and put it to the test in the context of automatic analysis of immunohistochemistry imagery for neural tissue analysis.
Description
Keywords
Fuzzy clustering, Image smoothing, Progressive supranuclear palsy
Department
Estadística, Informática y Matemáticas / Estatistika, Informatika eta Matematika
Faculty/School
Degree
Doctorate program
item.page.cita
Antunes-Santos, F., Lopez-Molina, C., Mir-Fuentes, A., Mendioroz, M., & De Baets, B. (2022). Content-aware image smoothing based on fuzzy clustering. En D. Ciucci, I. Couso, J. Medina, D. Ślęzak, D. Petturiti, B. Bouchon-Meunier, & R. R. Yager (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems (Vol. 1602, pp. 443-454). Springer International Publishing. https://doi.org/10.1007/978-3-031-08974-9_35
item.page.rights
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