Video Denoising Using Multiple Class Averaging with Multiresolution
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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