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New adaptive vector filter using fuzzy metrics

[+] Author Affiliations
Samuel Morillas

Technical University of Valencia, EPS Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de Gandia, Spain

Valentín Gregori

Technical University of Valencia, EPS Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de Gandia, Spain

Guillermo Peris-Fajarnés

Technical University of Valencia, EPS Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de Gandia, Spain

Almanzor Sapena

Technical University of Valencia, EPS Gandia, Carretera Nazaret-Oliva s/n, 46730 Grao de Gandia, Spain

J. Electron. Imaging. 16(3), 033007 (August 03, 2007). doi:10.1117/1.2767335
History: Received December 14, 2006; Revised March 30, 2007; Accepted April 02, 2007; Published August 03, 2007
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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.

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© 2007 SPIE and IS&T

Citation

Samuel Morillas ; Valentín Gregori ; Guillermo Peris-Fajarnés and Almanzor Sapena
"New adaptive vector filter using fuzzy metrics", J. Electron. Imaging. 16(3), 033007 (August 03, 2007). ; http://dx.doi.org/10.1117/1.2767335


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