Abstract
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.
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Morillas, S., Gregori, V., Riquelme, J., Defez, B., Peris-Fajarnés, G. (2007). Fuzzy Directional-Distance Vector Filter. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_45
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DOI: https://doi.org/10.1007/978-3-540-73400-0_45
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