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arXiv · 1710.02213

Video Denoising and Enhancement via Dynamic Video Layering

Han Guo·Namrata Vaswani
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Abstract

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.

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Han Guo, Namrata Vaswani. 2017-10-05. Video Denoising and Enhancement via Dynamic Video Layering. https://doi.org/10.1109/lsp.2018.2833429

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