Bayesian resolution enhancement of compressed video

Super-resolution algorithms recover high-frequency information from a sequence of low-resolution observations. In this paper, we consider the impact of video compression on the super-resolution task. Hybrid motion-compensation and transform coding schemes are the focus, as these methods provide obse...

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Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 13(2004), 7 vom: 23. Juli, Seite 898-911
1. Verfasser: Segall, C Andrew (VerfasserIn)
Weitere Verfasser: Katsaggelos, Aggelos K, Molina, Rafael, Mateos, Javier
Format: Aufsatz
Sprache:English
Veröffentlicht: 2004
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung:Super-resolution algorithms recover high-frequency information from a sequence of low-resolution observations. In this paper, we consider the impact of video compression on the super-resolution task. Hybrid motion-compensation and transform coding schemes are the focus, as these methods provide observations of the underlying displacement values as well as a variable noise process. We utilize the Bayesian framework to incorporate this information and fuse the super-resolution and post-processing problems. A tractable solution is defined, and relationships between algorithm parameters and information in the compressed bitstream are established. The association between resolution recovery and compression ratio is also explored. Simulations illustrate the performance of the procedure with both synthetic and nonsynthetic sequences
Beschreibung:Date Completed 10.02.2005
Date Revised 10.12.2019
published: Print
Citation Status MEDLINE
ISSN:1941-0042