ENCODER AND DECODER OPTIMIZATION FOR SOURCE-CHANNEL PREDICTION IN ERROR RESILIENT VIDEO TRANSMISSION (WA-L5)

Author(s) : Hua Yang (Electrical and Computer Engineering Department, University of California Santa Barbara, USA) Kenneth Rose (Electrical and Computer Engineering Department, University of California Santa Barbara, USA)

Abstract : Motion-compensated prediction that accounts for loss in the channel is achieved by the source-channel prediction (SCP) method, which is based on the expected decoder reconstruction of past frames (rather than their encoder reconstruction). The decoder reconstruction is estimated by exploiting the recursive optimal per-pixel estimate (ROPE), which explicitly accounts for the quantization distortion, channel loss, error propagation, as well as the decoder operation, and achieves improved error resilience. We take this paradigm further by noting that the decoder can, in turn, be re-optimized to match the modification introduced to the encoder. While it is theoretically beneficial to continue iterating encoder and decoder design, we show that, after one complete iteration, diminishing gains do not justify further increase in complexity. Simulation results demonstrate that substantial performance gains are achieved by one round of encoder and decoder optimization for source-channel prediction.

Menu