High-density impulse noise removal using fuzzy mathematical morphology

DOI

10.2991/eusflat.2013.109How to use a DOI?

Keywords

Mathematical morphology t-norm residual implication high probability impulse noise noise reduction nonlinear filter open-close filter

Abstract

This paper proposes a filtering method for high-density impulse noise removal based on the fuzzy mathematical morphology using t-norms. The method is a two phased method. In the first phase, an impulse noise detector based on the fuzzy top-hat transforms is used to identify pixels which are likely to be contaminated by noise. In the second phase, the image is restored using a specialized regularization method using fuzzy open-close or fuzzy close-open sequences applied only to those selected contaminated pixels and applying then a block smart erase algorithm. Experimental results show that the proposed algorithm presents a better performance in terms of edge preservation and noise suppression than other nonlinear filtering methods, including the presented in [1], in which this method is based on.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Manuel González-Hidalgo
AU  - Sebastià Massanet
AU  - Arnau Mir
AU  - Daniel Ruiz-Aguilera
PY  - 2013/08
DA  - 2013/08
TI  - High-density impulse noise removal using fuzzy mathematical morphology
BT  - Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
PB  - Atlantis Press
SP  - 768
EP  - 775
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2013.109
DO  - 10.2991/eusflat.2013.109
ID  - González-Hidalgo2013/08
ER  -