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Motion compensated prediction is central to the efficiency of videocompression. Its predictive coding scheme propagates the quantizationdistortion through the prediction chain and creates a temporal dependency.Prior research typically models the distortion propagation based on thesimilarity between original pixels under the assumption of high resolutionquantization. Its efficacy in the low to medium bit-rate range, where thequantization step size is largely comparable to the magnitude of the residualsignals, is questionable. This work proposes a quantitative approach toestimating the temporal dependency. It evaluates the rate and distortion foreach coding block using the original and the reconstructed motion compensationreference blocks, respectively. Their difference effectively measures how thequantization error in the reference block impacts the coding efficiency of thecurrent block. A recursive update process is formulated to track suchdependency through a group of pictures. The proposed scheme quantifies thetemporal dependency more accurately across a wide range of operating bit-rates,which translates into considerable coding performance gains over the existingcontenders as demonstrated in the experiments.

A Quantitative Approach To The Temporal Dependency in Video Coding