Learning priors for super-resolution in video sequence

Publication Type:
Conference Proceeding
Citation:
Proceedings of the 2nd International Conference on Internet Multimedia Computing and Service, ICIMCS'10, 2010, pp. 163 - 166
Issue Date:
2010-12-01
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Video becomes a crucial information resource in last decades, because of the rapid development of camera as well as the internet explosion. High-quality video sequences are always desired in lots of fields. Since the bottleneck of data storage and interferences of shooting condition, we cannot always obtain high-resolution video. This botheration can be circumvented by super-resolution. Currently, almost super-resolution techniques are in the framework of Maximum a Posterior (MAP). Appropriate parameters of prior distribution are crucial for recovering accurate super-resolution image. We utilise a novel Weighted Cross Validation (WCG) method to learn theses prior parameters. Comparison experiments are provided to illustrate the effectiveness of our approach. Copyright 2010 ACM.
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