Video denoising refers to the problem of removing "noise" from a videosequence. Here the term "noise" is used in a broad sense to refer to anycorruption or outlier or interference that is not the quantity of interest. Inthis work, we develop a novel approach to video denoising that is based on theidea that many noisy or corrupted videos can be split into three parts - the"low-rank layer", the "sparse layer", and a small residual (which is small andbounded). We show, using extensive experiments, that our denoising approachoutperforms the state-of-the-art denoising algorithms.
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