Lagrangian multiplier optimization using correlations in residues

Zhenyu Liu, Dongsheng Wang, Junwei Zhou, Takeshi Ikenaga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Rate distortion optimization (RDO) algorithm plays the vital role in the up to date hybrid video codec H.264/AVC. The RDO algorithm of H.264/AVC reference software is built up by assuming that the transformed residues are memoryless variables. However, our experiments reveal that, for some sequences, the strong temporal correlations exist in the prediction residues. This paper extends the Lagrangian optimization techniques by modeling the transformed residues as the first-order Markov source and calibrating the distortion model with the piecewise approximation function. The proposed algorithms adjust the Lagrangian multiplier dynamically to improve the overall coding quality. Comprehensive experiments testify that, as compared with the JM reference software, our optimizations can achieve up to 1.875dB coding gain. Moreover, our algorithms posses more robust coding performance and introduce less computational overhead than the Laplace distribution based methods. The inherent short process latency makes it possible to cooperate our algorithms with rate control operation. Last but not least, the proposed approach is also useful for the emerging standard, HEVC.

Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages1185-1188
Number of pages4
DOIs
Publication statusPublished - 2012
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto
Duration: 2012 Mar 252012 Mar 30

Other

Other2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
CityKyoto
Period12/3/2512/3/30

Fingerprint

Experiments

Keywords

  • H.264/AVC
  • HEVC
  • Hybrid Video Coding
  • Lagrangian Multiplier
  • Rate Distortion Optimization

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

Cite this

Liu, Z., Wang, D., Zhou, J., & Ikenaga, T. (2012). Lagrangian multiplier optimization using correlations in residues. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 1185-1188). [6288099] https://doi.org/10.1109/ICASSP.2012.6288099

Lagrangian multiplier optimization using correlations in residues. / Liu, Zhenyu; Wang, Dongsheng; Zhou, Junwei; Ikenaga, Takeshi.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2012. p. 1185-1188 6288099.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Liu, Z, Wang, D, Zhou, J & Ikenaga, T 2012, Lagrangian multiplier optimization using correlations in residues. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings., 6288099, pp. 1185-1188, 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012, Kyoto, 12/3/25. https://doi.org/10.1109/ICASSP.2012.6288099
Liu Z, Wang D, Zhou J, Ikenaga T. Lagrangian multiplier optimization using correlations in residues. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2012. p. 1185-1188. 6288099 https://doi.org/10.1109/ICASSP.2012.6288099
Liu, Zhenyu ; Wang, Dongsheng ; Zhou, Junwei ; Ikenaga, Takeshi. / Lagrangian multiplier optimization using correlations in residues. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2012. pp. 1185-1188
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