Map estimation of multiple description encoded video transmitted over noisy channels

The problem of efficient video transmission over noisy channels involves high compression rates and robustness to channel errors. In the framework of multiple description coding (MDC), we focus on the direct estimation of the source from two noisy descriptions, without trying to estimate the single descriptions. The challenge is to reconstruct a central signal with distortion as small as possible using the knowledge of the two noisy descriptions. We propose in this paper a maximum a posteriori (MAP) estimator for the decoding of the central description, using the knowledge of the probability density function (pdf) of the different subband descriptions. The balanced MDC scheme used for application is a scan-based wavelet transform video coding scheme, and includes an efficient bit allocation procedure that dispatches the source video redundancy between the different descriptions, depending on the characteristics of the channel. Simulation results show a good robustness of the proposed decoding scheme against transmission errors, with an improvement of 2 dB in PSNR compared to a maximum likelihood (ML) technique.