Referenced Items are not available for this document.
The traditional Lagrangian RDO algorithm assumes the transformed residues as memo- ryless random variables, and then doesn't perform well when the prediction residues posses the strong temporal correlations. We extend the RDO by modeling the residues as the first-order Markov source and calibrating the distortion model with the piecewise approximation function.
Published in:
Data Compression Conference (DCC), 2012
Date of Conference: 10-12 April 2012
- Page(s):
- 404
- ISSN :
- 1068-0314
- Print ISBN:
- 978-1-4673-0715-4
- INSPEC Accession Number:
- 12695713
- Conference Location :
- Snowbird, UT
- Digital Object Identifier :
- 10.1109/DCC.2012.59
- Product Type:
- Conference Publications
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