High-density impulse noise removal using fuzzy mathematical morphology
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- Mathematical morphology t-norm residual implication high probability impulse noise noise reduction nonlinear filter open-close filter
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 , in which this method is based on.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/eusflat.2013.109 ID - González-Hidalgo2013/08 ER -