Publication: Application of smooth fuzzy model in image denoising and edge detection
Loading...
Identifiers
Publication date
2022-07-02
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Impact
Export
Abstract
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.
Description
This article belongs to the Special Issue Soft Methods for Modeling Uncertainty and Imprecision.
Keywords
Bounded variation function, Edge detection, Fuzzy models, Noise reduction, Smooth compositions
Bibliographic citation
Sadjadi, 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.