Paper Info
Title
On the Decomposition of Interval-Valued Fuzzy Morphological Operators
Abstract
Interval-valued fuzzy mathematical morphology is an extension of classical fuzzy mathematical morphology, which is in turn one of the extensions of binary morphology to greyscale morphology. The uncertainty that may exist concerning the grey value of a pixel due to technical limitations or bad recording circumstances, is taken into account by mapping the pixels in the image domain onto an interval to which the pixel's grey value is expected to belong instead of one specific value. Such image representation corresponds to the representation of an interval-valued fuzzy set and thus techniques from interval-valued fuzzy set theory can be applied to extend greyscale mathematical morphology. In this paper, we study the decomposition of the interval-valued fuzzy morphological operators. We investigate in which cases the [驴 1,驴 2]-cuts of these operators can be written or approximated in terms of the corresponding binary operators. Such conversion into binary operators results in a reduction of the computation time and is further also theoretically interesting since it provides us a link between interval-valued fuzzy and binary morphology.
Year
DOI
Venue
2010
10.1007/s10851-009-0185-7
Journal of Mathematical Imaging and Vision
Keywords
Field
DocType
Interval-valued fuzzy sets,Mathematical morphology,Decomposition
Discrete mathematics,Mathematical optimization,Fuzzy classification,Defuzzification,Fuzzy set operations,Fuzzy logic,Algorithm,Fuzzy set,Fuzzy subalgebra,Fuzzy associative matrix,Fuzzy number,Mathematics
Journal
Volume
Issue
ISSN
36
3
0924-9907
Citations 
PageRank 
References 
5
0.40
12
Authors
4
Name
Order
Citations
PageRank
Tom Mélange1847.35
Mike Nachtegael240434.01
Peter Sussner388059.25
Etienne E. Kerre43909331.20