Error-resilient video transmission using long-term memory motion-compensated prediction

Long-term memory prediction extends the spatial displacement vector utilize d in hybrid video coding by a variable time delay, permitting the use of mo re than one reference frame for motion compensation. This extension leads t o improved rate-distortion performance. However, motion compensation in com bination with transmission errors leads to temporal error propagation that occurs when the reference frames at coder and decoder differ. In this paper , we present a framework that incorporates an estimated error into rate-con strained motion estimation and mode decision. Experimental results with a R ayleigh fading channel show that long-term memory prediction significantly outperforms the single-frame prediction H.263-based anchor. When a feedback channel is available, the decoder can inform the encoder about successful or unsuccessful transmission events by sending positive (ACK) or negative ( NACK) acknowledgments. This information is utilized for updating the error estimates at the encoder. Similar concepts, such as the ACK and NACK mode k nown from the H.263 standard, are unified into a general framework providin g superior transmission performance.