@article{schuster1997theory,
abstract = {In this paper, we address the fundamental problem of optimally splitting a video sequence into two sources of information, the displaced frame difference (DFD) and the displacement vector field (DVF). We first consider the case of a lossless motion-compensated video coder (MCVC), and derive a general dynamic programming (DP) formulation which results in an optimal tradeoff between the DVF and the DFD. We then consider the more important case of a lossy MCVC, and present an algorithm which solves the tradeoff between the rate and the distortion. This algorithm is based on the Lagrange multiplier method and the DP approach introduced for the lossless MCVC. We then present an H.263-based MCVC which uses the proposed optimal bit allocation, and compare its results to H.263. As expected, the proposed coder is superior in the rate-distortion sense. In addition to this, it offers many advantages for a rate control scheme. The presented theory can be applied to build new optimal coders, and to analyze the heuristics employed in existing coders. In fact, whenever one changes an existing coder, the proposed theory can be used to evaluate how the change affects its performance.},
author = {Schuster, G.M. and Katsaggelos, A.K.},
doi = {10.1109/49.650047},
issn = {07338716},
journal = {IEEE Journal on Selected Areas in Communications},
keywords = {Motion estimation,Optimal bit allocation,Quantizer selection,Rate-distortion theory,Video compression},
number = {9},
pages = {1739--1751},
publisher = {IEEE},
title = {{A theory for the optimal bit allocation between displacement vector field and displaced frame difference}},
url = {http://ieeexplore.ieee.org/document/650047/},
volume = {15},
year = {1997}
}

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We then present an H.263-based MCVC which uses the proposed optimal bit allocation, and compare its results to H.263. As expected, the proposed coder is superior in the rate-distortion sense. In addition to this, it offers many advantages for a rate control scheme. The presented theory can be applied to build new optimal coders, and to analyze the heuristics employed in existing coders. 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