Abstract
In this paper we present a novel video denoising method based on a fuzzy logic recursive motion detection scheme. For each pixel a fuzzy quantity (motion confidence) is calculated, indicating the membership degree of the fuzzy set “motion”. Next, this fuzzy quantity is used to perform adaptive temporal filtering, where the amount of filtering is inversely proportional to the determined membership degree. Since big motion changes reduce temporal filtering, a non-stationary noise will be introduced. Hence a new fuzzy spatial filter is applied subsequently in order to obtain the final denoised image sequence. Experimental results show that the proposed method outperform other state of the art non-multiscale video denoising techniques and are comparable with some multi-scale (wavelet) based video denoising techniques.
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Schulte, S., Zlokolica, V., Pizurica, A., Philips, W., Kerre, E. (2005). Noise Reduction of Video Sequences Using Fuzzy Logic Motion Detection. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_84
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DOI: https://doi.org/10.1007/11558484_84
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29032-2
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