Video denoising by fuzzy motion and detail adaptive averaging | Zendy

Tom Mélange | Zendy

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Video denoising by fuzzy motion and detail adaptive averaging

Author(s) -

Tom Mélange

Publication year - 2008

Publication title -

journal of electronic imaging

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.238

H-Index - 66

eISSN - 1560-229X

pISSN - 1017-9909

DOI - 10.1117/1.2992065

Subject(s) - video denoising , artificial intelligence , computer vision , fuzzy logic , adaptive filter , noise reduction , computer science , motion compensation , wavelet , pattern recognition (psychology) , motion estimation , grayscale , mathematics , pixel , algorithm , video processing , video tracking , multiview video coding

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.

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