Name
Abstract | ||
|---|---|---|
Context based entropy coding has the potential to provide higher gain over memoryless entropy coding. However serious difficulties arise regarding the practical implementation in real-time applications due to its very high memory requirements. This paper presents an efficient method for designing context adaptive entropy coding while fulfilling low memory requirements. From a study of coding gain scalability as a function of context size, new context design and validation procedures are derived. Further, supervised clustering and mapping optimization are introduced to model efficiently the context. The resulting context modelling associated with an arithmetic coder was successfully implemented in a transform-based audio coder for real-time processing. It shows significant improvement over the entropy coding used in MPEG-4 AAC. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICASSP.2011.5946448 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
arithmetic codes,audio coding,entropy codes,memoryless systems,optimisation,MPEG-4 AAC,arithmetic coder,context adaptive entropy coding,context design,context modelling,context validation procedure,memory requirement,memoryless entropy coding gain scalability,real-time processing,supervised clustering,supervised mapping optimization,transform-based audio coder,Entropy coding,audio coding,context modelling | Coding gain,Entropy encoding,Computer science,Context-adaptive variable-length coding,Context model,Theoretical computer science,Memory management,Cluster analysis,Context-adaptive binary arithmetic coding,Scalability | Conference |
ISSN | ISBN | Citations |
1520-6149 E-ISBN : 978-1-4577-0537-3 | 978-1-4577-0537-3 | 7 |
PageRank | References | Authors |
0.86 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guillaume Fuchs | 1 | 38 | 7.84 |
| Vignesh Subbaraman | 2 | 9 | 1.93 |
| Markus Multrus | 3 | 36 | 4.06 |