Fuzzy Directional-Distance Vector Filter

Authors:
Samuel Morillas;Valentín Gregori;Julio Riquelme;Beatriz Defez;Guillermo Peris-Fajarnés
Affiliations:
Universidad Politécnica de Valencia, E.P.S. de Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de Gandia (Valencia), Spain;Universidad Politécnica de Valencia, E.P.S. de Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de Gandia (Valencia), Spain;Universidad Politécnica de Valencia, E.P.S. de Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de Gandia (Valencia), Spain;Universidad Politécnica de Valencia, E.P.S. de Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de Gandia (Valencia), Spain;Universidad Politécnica de Valencia, E.P.S. de Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de Gandia (Valencia), Spain
Venue:
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Year:
2007

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Abstract

A well-known family of nonlinear multichannel image filters uses the ordering of vectors by means of an appropriate distance or similarity measurebetween 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 metricis used to measure magnitude and directional fuzzy distancesbetween image vectors. Then, a variant of the DDF using this fuzzy metricis 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.