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Applying Open-Loop Coding in Predictive Coding Systems

  • Adrian Munteanu
  • Frederik Verbist
  • Jan Cornelis
  • Peter Schelkens
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5259)

Abstract

This paper investigates the application of open-loop coding principles in predictive coding systems. In order to cope with the drift, which is inherent in open-loop predictive coding, a novel rate-distortion (R-D) model is proposed, capturing the propagation of quantization errors in such systems. Additionally, a novel intra-frame video codec employing the transform and spatial prediction modes from H.264 is proposed. The results obtained with the proposed codec show that allocating rate based on the proposed R-D model provides gains of up to 1.9 dB compared to a straightforward rate allocation not accounting for drift. Furthermore, the proposed open-loop predictive codec provides gains of up to 2.3 dB compared to an equivalent closed-loop intra-frame video codec using the transform, prediction modes and rate-allocation from H.264. One concludes that the considered open-loop predictive coding paradigm retains the advantages of open-loop coding, and offers the possibility of further improving the compression performance in predictive coding systems.

Keywords

Quantization Error Prediction Mode Scalable Video Code Rate Allocation Reference Source 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Wiegand, T., Sullivan, G.J., Bjontegaard, G., Luthra, A.: Overview of the H. 264/AVC Video Coding Standard. IEEE Transactions on Circuits and Systems for Video Technology 13(7), 560–576 (2003)CrossRefGoogle Scholar
  2. 2.
    Richardson, I.E.G.: H. 264 and MPEG-4 Video Compression. Wiley, UK (2003)CrossRefGoogle Scholar
  3. 3.
    Chen, P., Woods, J.W.: Bidirectional MC-EZBC with lifting implementation. IEEE Transactions for Circuits and Systems for Video Technology 14, 1183–1194 (2004)CrossRefGoogle Scholar
  4. 4.
    Andreopoulos, Y., Munteanu, A., Barbarien, J., Van der Schaar, M., Cornelis, J., Schelkens, P.: In-band motion compensated temporal filtering. Signal Processing: Image Communication 19(7), 653–673 (2004)Google Scholar
  5. 5.
    Schwarz, H., Marpe, D., Wiegand, T.: Overview of the scalable video coding extension of the H. 264/AVC standard. IEEE Transactions for Circuits and Systems for Video Technology 17(9), 1103–1120 (2007)CrossRefGoogle Scholar
  6. 6.
    Ohm, J.-R.: Advances in scalable video coding. Proceedings of the IEEE 93, 42–56 (2005)CrossRefGoogle Scholar
  7. 7.
    Rusert, T., Ohm, J.-R.: Backward drift estimation with application to quality layer assignment in H.264/AVC based scalable video coding. In: Int. Conf. Acoustics, Speech and Signal Processing, ICASSP 2007, Hawaii, USA, vol. I, pp. 653–656 (April 2007)Google Scholar
  8. 8.
    Everett, H.: Generalized Lagrange multiplier method for solving problems of optimal allocation of resources. Operation Research 11, 399–417 (1963)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Gersho, A., Gray, R.M.: Vector Quantization and Signal Compression. Kluwer Academic Publishers, Norwell (1992)CrossRefzbMATHGoogle Scholar
  10. 10.
    Bjontegaard, G.: Calculation of average PSNR differences between RD-curves, ITU-T Video Coding Experts Group (VCEG), Austin, USA, Document VCEG-M33 (April 2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Adrian Munteanu
    • 1
  • Frederik Verbist
    • 1
  • Jan Cornelis
    • 1
  • Peter Schelkens
    • 1
  1. 1.Department of Electronics and Informatics – Interdisciplinary Institute for Broadband TechnologyVrije Universiteit BrusselBrusselsBelgium

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