Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework

Aniello Fiengo (1) , Giovanni Chierchia (2) , Marco Cagnazzo (1) , Béatrice Pesquet-Popescu (1)

1 LTCI - Laboratoire Traitement et Communication de l'Information
2 LIGM - Laboratoire d'Informatique Gaspard-Monge

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, using a recursive rate-distortion model that explicitly takes into account these dependencies, we approach the frame-level rate allocation as a convex optimization problem. This technique is integrated into the recent HEVC encoder, and tested on several standard sequences. Experiments indicate that the proposed rate allocation ensures a better performance (in the rate-distortion sense) than the standard HEVC rate control, and with a little loss w.r.t. an optimal exhaustive research which is largely compensated by a much shorter execution time.

Mots clés: Video coding; rate distortion; convex optimization; bit allocation

Domaines: Théorie de l'information et codage [math.IT]; Optimisation et contrôle [math.OC]

Aniello Fiengo, Giovanni Chierchia, Marco Cagnazzo, Béatrice Pesquet-Popescu. Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework. IEEE Transactions on Image Processing, 2017, 26 (1), pp.479 - 489. ⟨10.1109/TIP.2016.2621666⟩. ⟨hal-01718496⟩