Video denoising by fuzzy motion and detail adaptive averaging

Tom Mélange; Mike Nachtegael; Etienne E. Kerre; Vladimir Zlokolica; Stefan Schulte; Valerie De Witte; Aleksandra Pizurica; Wilfried R. Philips

doi:10.1117/1.2992065

1 October 2008 Video denoising by fuzzy motion and detail adaptive averaging

Tom Mélange, Mike Nachtegael, Etienne E. Kerre, Vladimir Zlokolica, Stefan Schulte, Valerie De Witte, Aleksandra Pizurica, Wilfried R. Philips

Author Affiliations +

Journal of Electronic Imaging, Vol. 17, Issue 4, 043005 (October 2008). https://doi.org/10.1117/1.2992065

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.

©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Tom Mélange, Mike Nachtegael, Etienne E. Kerre, Vladimir Zlokolica, Stefan Schulte, Valerie De Witte, Aleksandra Pizurica, and Wilfried R. Philips "Video denoising by fuzzy motion and detail adaptive averaging," Journal of Electronic Imaging 17(4), 043005 (1 October 2008). https://doi.org/10.1117/1.2992065

Published: 1 October 2008

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