Noisy video super-resolution

Authors:
Feng Liu;Jinjun Wang;Shenghuo Zhu;Michael Gleicher;Yihong Gong
Affiliations:
University of Wisconsin-Madison, Madison, WI, USA;NEC Laboratories America, Inc., Cuptertino, CA, USA;NEC Laboratories America, Inc., Cuptertino, CA, USA;University of Wisconsin-Madison, Madison, WI, USA;NEC Laboratories America, Inc., Cuptertino, CA, USA
Venue:
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Year:
2008

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Abstract

Low-quality videos often not only have limited resolution, but also suffer from noise. Directly up-sampling a video without considering noise could deteriorate its visual quality due to magnifying noise. This paper addresses this problem with a unified framework that achieves simultaneous de-noising and super-resolution. This framework formulates noisy video super-resolution as an optimization problem, aiming to maximize the visual quality of the result. We consider a good quality result to be fidelity-preserving, detail-preserving and smooth. Accordingly, we propose measures for these qualities in the scenario of de-noising and super-resolution. The experiments on a variety of noisy videos demonstrate the effectiveness of the presented algorithm.