RT Journal Article
T1 Application of smooth fuzzy model in image denoising and edge detection
A1 Sadjadi, Ebrahim
A1 Sadrian Zadeh, Danial
A1 Moshiri, Behzad
A1 García Herrero, Jesús
A1 Molina López, José Manuel
A1 Fernández, Roemi
AB In 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.
PB MDPI
SN 2227-7390
YR 2022
FD 2022-07-02
LK https://hdl.handle.net/10016/37033
UL https://hdl.handle.net/10016/37033
LA eng
NO This article belongs to the Special Issue Soft Methods for Modeling Uncertainty and Imprecision.
NO This 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.
DS e-Archivo
RD 30 jun. 2024