Paper Info
Title
High-density impulse noise removal using fuzzy mathematical morphology.
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 tophat 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.
Year
Venue
Keywords
2013
PROCEEDINGS OF THE 8TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT-13)
Mathematical morphology,t-norm,residual implication,high probability impulse noise,noise reduction,nonlinear filter,open-close filter
Field
DocType
Volume
Computer vision,Fuzzy logic,Fuzzy mathematical morphology,Filter (signal processing),Algorithm,Regularization (mathematics),Impulse noise,Artificial intelligence,Pixel,TopHat,Detector,Mathematics
Conference
32.0
ISSN
Citations 
PageRank 
1951-6851
3
0.42
References 
Authors
17
4
Name
Order
Citations
PageRank
Manuel González Hidalgo19918.29
Sebastià Massanet243834.95
Arnau Mir35914.40
Daniel Ruiz-Aguilera434525.56