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Journal of Electronic Imaging

New adaptive vector filter using fuzzy metrics
Author(s): Samuel Morillas; Valentin Gregori; Guillermo Peris-Fajarnes; Almanzor Sapena
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Paper Abstract

Classical nonlinear vector median-based filters are well-known methods for impulsive noise suppression in color images, but mostly they lack good detail-preserving ability. We use a class of fuzzy metrics to introduce a vector filter aimed at improving the detail-preserving ability of classical vector filters while effectively removing impulsive noise. The output of the proposed method is the pixel inside the filter window which maximizes the similarity in color and spatial closeness. The use of fuzzy metrics allows us to handle both criteria simultaneously. The filter is designed so that the importance of the spatial criterion can be adjusted. We show that the filter can adapt to the density of the contaminating noise by adjusting the spatial criterion importance. Classical and recent filters are used to assess the proposed filtering. The experimental results show that the proposed technique performs competitively.

Paper Details

Date Published: 1 July 2007
PDF: 15 pages
J. Electron. Imaging. 16(3) 033007 doi: 10.1117/1.2767335
Published in: Journal of Electronic Imaging Volume 16, Issue 3
Show Author Affiliations
Samuel Morillas, Univ. Politècnica de València (Spain)
Valentin Gregori, Univ. Politècnica de València (Spain)
Guillermo Peris-Fajarnes, Univ. Politècnica de València (Spain)
Almanzor Sapena, Univ. Politècnica de València (Spain)


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