Error resilient video coding via weighted distortion
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Adaptive resynchronization approach for scalable video over wireless channel
Journal of Visual Communication and Image Representation
Optimizing motion compensated prediction for error resilient video coding
IEEE Transactions on Image Processing
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This paper proposes a complete stochastic framework for RD optimal encoder design for video over error-prone networks, which applies to any motion-compensated predictive video codec. The distortion measure has been taken as the mean square error over an ensemble of channels given an estimate of the instantaneous packet loss probability. We show that 1) the optimal motion compensated prediction, in the MSE sense, requires computation of the expected value of the reference frames, and 2) calculation of the MSE (distortion measure) requires computation of the second moment of the reference frames. We propose a recursive procedure for the computation of both the expected value and second moment of the reference frames, which are together called the stochastic frame buffer. Furthermore, we propose a stochastic RD optimization method for selection of the optimal macroblock mode and motion vectors given the instantaneous packet loss probability. If available, channel feedback can also be incorporated into the proposed stochastic framework. However, the proposed framework does not require a feedback channel to exist, and when it exists, it does not have to be lossless. In the absence of any packet losses, the proposed stochastic framework reduces to the well-known deterministic RD optimization procedures. One possible application of the optimal stochastic framework would be for multicast streaming to an ensemble of receivers. Experimental results indicate that the proposed framework outperforms other available error tracking and control schemes