A convex-optimization framework for frame-level optimal rate allocation in predictive video coding

Optimal rate allocation is among the most challenging tasks to perform in the context of predictive video coding, because of the dependencies between frames induced by motion compensation. In this paper, we derive an analytical rate-distortion model that explicitly takes into account the dependencies between frames. The proposed approach allows us to formulate the frame-level optimal rate allocation as a convex optimization problem. Within this framework, we are able to achieve the exact solution in limited time (even for large-size problems), thanks to the flexibility offered by recent convex optimization techniques. Experiments on standard sequences demonstrate the interest of considering the proposed rate-distortion model and confirm that the optimal rate allocation ensures a better distribution of the total bit budget, with superior results (in the rate-distortion sense) with respect to the standard H.264/AVC rate control.