Abstract
This paper presents a non-linear technique for noise reduction in video that is suitable for real-time processing. The proposed algorithm automatically adapts to detected levels of detail and motion, but also to the noise level, provided it is short-tail noise, such as Gaussian noise. It uses a one-level wavelet decomposition, and performs independent processing in four different bands in the wavelet domain. The non-decimated transform is used because it leads to better results for image/video denoising than the decimated transform. The results show that from both a PSNR and a visual quality, the proposed filter outperforms the other state of the art filters for different image sequences.
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© 2003 Springer-Verlag Berlin Heidelberg
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Zlokolica, V., Pizurica, A., Philips, W. (2003). Video Denoising Using Multiple Class Averaging with Multiresolution. In: GarcÃa, N., Salgado, L., MartÃnez, J.M. (eds) Visual Content Processing and Representation. VLBV 2003. Lecture Notes in Computer Science, vol 2849. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39798-4_23
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DOI: https://doi.org/10.1007/978-3-540-39798-4_23
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