Work

Generalized Fuzzy Transform and Nonlocal Laplace Operator

Year: 2024

Type: article

Abstract: The F-transform has proven to be effective in various applications, such as time series analysis, numerical solutions of differential equations, and signal or image processing. The most important parameter of the F-transform is a fuzzy partition initially introduced for 1-D spaces, with a few generalizations to higher dimensional spaces. However, these generalizations have a limited application to signals defined on domains with arbitrary geometry. To overcome this limitation, we propose using nonseparable membership functions induced by kernels, allowing the application of the F-transform to more general domains. We introduce a universal concept of a fuzzy partition that includes a kernel representation, a fuzzy partition, and the corresponding F-transform. In addition, we discuss the main properties of this generalized F-transform and characterize the nonlocal Laplace operator in terms of the F-transform. We also discuss image denoising as the main application and compare our results with state-of-the-art methods and different noise types and intensities.

Source: IEEE Transactions on Fuzzy Systems

DOI: 10.1109/tfuzz.2024.3489227

Authors: Hana Zámečníková, Simone Cammarasana, Irina Perfilieva, Giuseppe Patané

Institutions: University of Ostrava, Istituto di Matematica Applicata e Tecnologie Informatiche, National Research Council

Language: English

Topic: Image and Signal Denoising Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,495

Funder: Ministero dell'Università e della Ricerca