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A Robust Fine Granularity Scalability Using Trellis-Based Predictive Leak

A Robust Fine Granularity Scalability Using Trellis-Based Predictive Leak. Hsiang-Chun Huang, Chung-Neng Wang and Tihao Chiang. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 12, NO. 6, JUNE 2002. Outline. Introduction Prediction techniques for the enhancement layer

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A Robust Fine Granularity Scalability Using Trellis-Based Predictive Leak

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  1. A Robust Fine Granularity Scalability Using Trellis-Based Predictive Leak Hsiang-Chun Huang, Chung-Neng Wang and Tihao Chiang IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 12, NO. 6, JUNE 2002

  2. Outline • Introduction • Prediction techniques for the enhancement layer • RFGS system architecture • Selection of the RFGS parameters • Experiment result and analyses • Conclusion

  3. Introduction • base layer and enhancement layer • High-quality reference frame • Error propagation and drift • Balance of coding efficiency and error robustness

  4. Prediction techniques for the enhancement layer • MPEG-4 FGS : the best error robustness • SNR scalable approach : the best coding efficiency • Robust FGS(RFGS) : strike a balance between these two approach

  5. Prediction techniques for the enhancement layer (cont.) • Two MC prediction techniques : • Leaky Prediction : 0α1 used to speed up the decay of error energy in the temporal directions • Partial Prediction : 0βmaximal number of bitplanes 1.βincreased, improved coding efficiency 2.βbitplanes is lost, the error will be attenuated by αtimes for each frame at the enhancement layer

  6. RFGS system architecture-base layer

  7. RFGS system architecture-enhancement layer

  8. RFGS system architecture-generate high quality base layer reference

  9. Selection of the RFGS parameters • Average weighted difference (AWD) • Use a linear model for computing the near-optimal α

  10. Selection of the RFGS parameters (cont.)

  11. Selection of the RFGS parameters (cont.) • Performance is better when 2-4 bitplanes are used for coding • Identical β is better than distinct β • β = 2 when bandwidth512K • β = 3 when bandwidth1.2M • β = 4 when bandwidth is even higher

  12. Experiment result and analyses

  13. Experiment result and analyses (cont.)

  14. Conclusions • Proposed a novel FGS coding technique RFGS • Leaky and partial predictions • Achieve a balance between coding efficiency, error robustness, and bandwidth adaptation

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