Speaker: Han Guo, ECpE Graduate Student
Advisor: Namrata Vaswani
Title: Video Denoising and Enhancement via Dynamic Sparse + Low-Rank Matrix Decomposition
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 everything else (which is small and bounded). We show, using extensive experiments, that our denoising approach outperforms the state-of-the-art denoising algorithms.