Estimating encoding complexity of a real-time embedded software HEVC codec

Alexandre Mercat 1 Wassim Hamidouche 1 Maxime Pelcat 2, 1 Daniel Menard 1
1 IETR - Institut d'Electronique et de Télécommunications de Rennes
2 IP - Institut Pascal
Abstract : The High Efficiency Video Coding (HEVC) standard provides up to 40% bitrate savings compared to the state-of-art H.264/AVC standard for the same perceptual video quality. Power consumption constraints represent a serious challenge for embedded applications based on a software design. A large number of systems are likely to integrate the HEVC codec in the long run and will need to be energy aware. In this context, we carry out a complexity study of the HEVC coding trees encoding process. This study shows that the complexity of encoding a Coding Unit (CU) of a given size has a non trivial probability density shape and thus can hardly be predicted with accuracy. However, we propose a model that linearly links the ratios between the complexities of coarse-grain and lower-grain CU encodings with a precision error under 6%. This model is valid for a wide range of video contents coded in Intra configurations at different bitrates. This information is useful to control encoder energy during the encoding process on battery limited devices.
Type de document :
Communication dans un congrès
Conference on Design and Architectures for Signal and Image Processing (DASIP), Oct 2016, Rennes, France. 〈10.1109/DASIP.2016.7853792〉
Liste complète des métadonnées
https://hal.archives-ouvertes.fr/hal-01498474
Contributeur : Daniel Menard <>
Soumis le : jeudi 30 mars 2017 - 10:22:49
Dernière modification le : mercredi 16 mai 2018 - 11:23:50

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IETR | UNIV-NANTES | SIGMA-CLERMONT | PRES_CLERMONT | INSTITUT_PASCAL | IETR-VAADER | IETR-INSA | UR1-UFR-ISTIC | UNIV-RENNES

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Alexandre Mercat, Wassim Hamidouche, Maxime Pelcat, Daniel Menard. Estimating encoding complexity of a real-time embedded software HEVC codec. Conference on Design and Architectures for Signal and Image Processing (DASIP), Oct 2016, Rennes, France. 〈10.1109/DASIP.2016.7853792〉. 〈hal-01498474〉

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