A Filter To Remove Gaussian Noise by Clustering the Gray Scale

Authors:
Zakaria Atae-Allah;José Martínez Aroza
Affiliations:
Dept. Matemática Aplicada, Universidad de Granada, Spain, Facultad de Ciencias, Avda. Fuentenueva s/n, 18071 Granada, Spain;Dept. Matem´atica Aplicada, Universidad de Granada, Spain, Facultad de Ciencias, Avda. Fuentenueva s/n, 18071 Granada, Spain jmaroza@ugr.es
Venue:
Journal of Mathematical Imaging and Vision
Year:
2002

Citing 3
Cited 2

Algorithms for clustering data

Algorithms for clustering data
The weighted median filter

Communications of the ACM
Pattern Recognition, Third Edition

Pattern Recognition, Third Edition

An Algorithm for Adaptive Mean Filtering and Its Hardware Implementation

Journal of VLSI Signal Processing Systems
Adaptive binarization method for enhancing ancient malay manuscript images

AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

An algorithm to suppress Gaussian noise is presented, based on clustering (grouping) gray levels. The histogram of a window sliding across the image is divided into clusters, and the algorithm outputs the mean level of the group containing the central pixel of the window. This filter restores well the majority of noisy pixels, leaving only few of them very deviated, that can be finally restored with a common filter for impulsive noise, such as a median filter. In this paper the clustering filter CF is described, analysed and compared with other similar filters.