Abstract
Image noise can be viewed as unwanted disturbances in a digital image that should be removed or reduced before further processing and analysis. Impulsive noise, also known as impulse noise, is a very disruptive type of noise, characterized by abrupt variations in brightness in a subset of the image pixels. Impulsive noise commonly occurs during image acquisition and transmission. To mitigate its effects, various impulsive noise reduction methods have been proposed by the image processing community. In contrast to classical filters such as the median filter, most current impulsive noise reduction techniques implement a two-step approach that consists of a noise detection phase to identify noisy pixels and a filtering phase to reduce the amount of noise in the presumably corrupted pixels.
The approach presented in this paper is also along this line. To be more precise, we draw on the principles of two state-of-the-art impulsive noise reduction methods, namely the adaptive fuzzy transform based image filter (ATIF) and the improved fuzzy mathematical morphology open-close filter (i-FMMOCS), in order to propose a new method for general impulsive noise reduction.
Supported in part by CNPq under grant no. 315638/2020-6 (“Lattice Computing with an Emphasis on \(\mathbb {L}\)-Fuzzy Systems and Mathematical Morphology”) and FAPESP under grant no. 2020/09838-0 (Brazilian Institute of Data Science) as well as the Grant PID2020-113870GB-I00-“Desarrollo de herramientas de Soft Computing para la Ayuda al Diagnóstico Clínico y a la Gestión de Emergencias (HESOCODICE)”, funded by MCIN/AEI/10.13039/501100011033/.
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Sussner, P., González-Hidalgo, M. (2023). FIDOC: A New Combination of Fuzzy Impulse Noise Detection and Open-Close Filtering. In: Massanet, S., Montes, S., Ruiz-Aguilera, D., González-Hidalgo, M. (eds) Fuzzy Logic and Technology, and Aggregation Operators. EUSFLAT AGOP 2023 2023. Lecture Notes in Computer Science, vol 14069. Springer, Cham. https://doi.org/10.1007/978-3-031-39965-7_19
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