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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Fuzzy Directional-Distance Vector Filter
verfasst von : Samuel Morillas, Valentín Gregori, Julio Riquelme, Beatriz Defez, Guillermo Peris-Fajarnés
Erschienen in: Applications of Fuzzy Sets Theory
Verlag: Springer Berlin Heidelberg
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A well-known family of nonlinear multichannel image filters uses the ordering of vectors by means of an appropriate
distance or similarity measure
between vectors. In this way, the
vector median filter
(VMF), the
vector directional filter
(VDF) and the
distance directional filter
(DDF) use the relative magnitude differences between vectors, the directional vector difference or a combination of both, respectively. In this paper, a novel
fuzzy metric
is used to measure magnitude and directional
fuzzy distances
between image vectors. Then, a variant of the DDF using this
fuzzy metric
is proposed. The proposed variant is computationally cheaper than the classical DDF. In addition, experimental results show that the proposed filter receives better results in impulsive noise suppression in colour images.