Decoding Energy Modeling for the Next Generation Video Codec Based on JEM

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Details zur Publikation

Autor(en): Herglotz C, Kränzler M, Kaup A
Jahr der Veröffentlichung: 2018
Sprache: Englisch


Abstract

This paper shows that the processing energy of the decoder software for the next generation video codec can be  accurately estimated using a feature based model. Therefore, a model from the literature is taken and extended to account for a high amount of the newly introduced coding modes. It is shown that using a selected set of 60 features, for a large set of more than 800 coded bit streams, a mean estimation error below 5% can be reached. Using the trained parameters of the model, the energy consumption of the decoder can be analyzed in detail such that, e.g., the coding modes consuming most processing energy can be identified. The model can be used inside the encoder for decoding-energy-rate-distortion optimization to generate decoding energy saving bit streams.


FAU-Autoren / FAU-Herausgeber

Herglotz, Christian Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Kaup, André Prof. Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Kränzler, Matthias
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


Zitierweisen

APA:
Herglotz, C., Kränzler, M., & Kaup, A. (2018). Decoding Energy Modeling for the Next Generation Video Codec Based on JEM. San Francisco, US.

MLA:
Herglotz, Christian, Matthias Kränzler, and Andre Kaup. "Decoding Energy Modeling for the Next Generation Video Codec Based on JEM." Proceedings of the Picture Coding Symposium (PCS), San Francisco 2018.

BibTeX: 

Zuletzt aktualisiert 2018-11-08 um 02:31