Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Error Control Coding, Second Edition
Error Control Coding, Second Edition
On-demand QoS multipath routing
ICCS '02 Proceedings of the The 8th International Conference on Communication Systems - Volume 01
Priority encoding transmission
IEEE Transactions on Information Theory - Part 1
Multiple-description vector quantization with lattice codebooks: design and analysis
IEEE Transactions on Information Theory
Generalized multiple description coding with correlating transforms
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Image Processing
Overview of fine granularity scalability in MPEG-4 video standard
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Multiple description coded video streaming in peer-to-peer networks
Image Communication
Multiple description coding for SNR scalable video transmission over unreliable networks
Multimedia Tools and Applications
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In this paper, we propose a novel 2-D layered multiple description coding (2DL-MDC) for error-resilient video transmission over unreliable networks. The proposed 2DL-MDC scheme allocates multiple description sub-bitstreams of a 2-D scalable bitstream to two network paths with unequal loss rates. We formulate the 2-D scalable rate-distortion problem and derive the expected distortion for the proposed scheme. To minimize the end-to-end distortion given the total rate budget and packet loss probabilities, we need to optimally allocate source and channel rates for each hierarchical sublayer of the scalable bitstream. The conventional Lagrangian multiplier method can be utilized to solve this problem but with overwhelming computational complexity. Therefore, we consider the use of the genetic algorithm to solve the rate-distortion optimization problem. The simulation results verify that the proposed method is able to achieve significant performance gain as opposed to the conventional equal rate allocation method.