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In this paper, we combine two powerful tools to handle the video denoising problem: one is an effective video denoising method based on highly sparse signal representation in local 3D transform domain, and the other is a low-rank matrix completion based video denoising method. Similarly, in our algorithm, a noisy video is processed in block-wise manner and for each processed block we form a 3D data array that we call “group” by stacking together blocks found similar to the currently processed one. “Collaborative filtering” exploits the correlation between grouped blocks and the corresponding highly sparse representation of the true signal in the transform domain. By employ low-rank matrix completion method in our framework, our technique is also robust to different types of noise, such as Gaussian additive noise and impulsive noise. Experiments demonstrate that our techniques produce state-of-the-art results for video denoising

Video Denoising based on Sparse Transformation and Low Rank Matrix Completion