A framework for adaptive scalable video coding using Wyner-Ziv techniques
EURASIP Journal on Applied Signal Processing
Mobility management for multi-user sessions in next generation wireless systems
Computer Communications
QoS mapping and adaptation control for multi-user sessions over heterogeneous wireless networks
Proceedings of the 3rd international conference on Mobile multimedia communications
Qos support for multi-user sessions in IP-based next generation networks
Mobile Networks and Applications
An integrated approach to control the quality level of multi-user sessions
Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops
Scalable Multimedia Group Communications through the Over-Provisioning of Network Resources
MMNS '08 Proceedings of the 11th IFIP/IEEE international conference on Management of Multimedia and Mobile Networks and Services: Management of Converged Multimedia Networks and Services
Information Sciences: an International Journal
A receiver-driven adaptive mechanism based on the popularity of scalable sessions
QofIS'02/ICQT'02 Proceedings of the 3rd international conference on quality of future internet services and internet charging and QoS technologies 2nd international conference on From QoS provisioning to QoS charging
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A method is proposed for efficient scalability in predictive coding, which overcomes known fundamental shortcomings of the prediction loop at enhancement layers. The compression efficiency of an enhancement-layer is substantially improved by casting the design of its prediction module within an estimation-theoretic framework, and thereby exploiting all information available at that layer for the prediction of the signal, and encoding of the prediction error. While the most immediately important application is in video compression, the method is derived in a general setting and is applicable to any scalable predictive coder. Thus, the estimation-theoretic approach is first developed for basic DPCM compression and demonstrates the power of the technique in a simple setting that only involves straightforward prediction, scalar quantization, and entropy coding. Results for the scalable compression of first-order Gauss-Markov and Laplace-Markov signals illustrate the performance. A specific estimation algorithm is then developed for standard scalable DCT-based video coding. Simulation results show consistent and substantial performance gains due to optimal estimation at the enhancement-layers