  Video denoising refers to the problem of removing "noise" from a video
sequence. Here the term "noise" is used in a broad sense to refer to any
corruption or outlier or interference that is not the quantity of interest. In
this work, we develop a novel approach to video denoising that is based on the
idea 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 and
bounded). We show, using extensive experiments, that our denoising approach
outperforms the state-of-the-art denoising algorithms.
