Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework

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, w...

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Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 26(2017), 1 vom: 15. Jan., Seite 479-489
1. Verfasser: Fiengo, Aniello (VerfasserIn)
Weitere Verfasser: Chierchia, Giovanni, Cagnazzo, Marco, Pesquet-Popescu, Beatrice
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2017
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article
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520 |a 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 with respect to an optimal exhaustive research, which is largely compensated by a much shorter execution time 
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