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Journal of Electronic Imaging

Video denoising by fuzzy motion and detail adaptive averaging
Author(s): Tom Mélange; Mike Nachtegael; Etienne E. Kerre; Vladimir Zlokolica; Stefan Schulte; Valerie De Witte; Aleksandra Pizurica; Wilfried R. Philips
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Paper Abstract

A new fuzzy-rule-based algorithm for the denoising of video sequences corrupted with additive Gaussian noise is presented. The proposed method constitutes a fuzzy-logic-based improvement of a recent detail and motion adaptive multiple class averaging filter (MCA). The method is first explained in the pixel domain for grayscale sequences, and is later extended to the wavelet domain and to color sequences. Experimental results show that the noise in digital image sequences is efficiently removed by the proposed fuzzy motion and detail adaptive video filter (FMDAF), and that the method outperforms other state of the art filters of comparable complexity on different video sequences.

Paper Details

Date Published: 1 October 2008
PDF: 19 pages
J. Electron. Imaging. 17(4) 043005 doi: 10.1117/1.2992065
Published in: Journal of Electronic Imaging Volume 17, Issue 4
Show Author Affiliations
Tom Mélange, Univ. Ghent (Belgium)
Mike Nachtegael, Univ. Gent (Belgium)
Etienne E. Kerre, Univ. Gent (Belgium)
Vladimir Zlokolica, Univ. Gent (Belgium)
Stefan Schulte, Traficon N.V. (Belgium)
Valerie De Witte, Univ. Gent (Belgium)
Aleksandra Pizurica, Univ. Gent (Belgium)
Wilfried R. Philips, Univ. Gent (Belgium)

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