Abstract
In this paper a new low-complexity algorithm for the denoising of video sequences is presented. The proposed fuzzy-rule based algorithm is first explained in the pixel domain and later extended to the wavelet domain. The method can be seen as a fuzzy variant of a recent multiple class video denoising method that automatically adapts to detail and motion. Experimental results show that the proposed algorithm efficiently removes Gaussian noise from digital greyscale image sequences. These results also show that our method outperforms other state-of-the-art filters of comparable complexity for different video sequences.
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Mélange, T. et al. (2007). A New Fuzzy Motion and Detail Adaptive Video Filter. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_58
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DOI: https://doi.org/10.1007/978-3-540-74607-2_58
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