- Title
- Learning priors for super-resolution in video sequence
- Creator
- Peng, Yu; Jin, Jesse S.; Luo, Suhuai; Xu, Min
- Relation
- 2nd International Conference on Internet Multimedia Computing and Service (ICIMCS 2010). ICIMCS '10: Proceedings of the Second International Conference on Internet Multimedia Computing and Service (Harbin, China 30-31 December, 2010) p. 163-166
- Publisher Link
- http://dx.doi.org/10.1145/1937728.1937767
- Publisher
- ACM
- Resource Type
- conference paper
- Date
- 2010
- Description
- 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.
- Subject
- super-resolution; prior distribution; weighted cross validation
- Identifier
- http://hdl.handle.net/1959.13/927296
- Identifier
- uon:10102
- Identifier
- ISBN:9781450304603
- Language
- eng
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