Decoding-Energy-Rate-Distortion Optimization for Video Coding

This paper presents a method for generating coded video bit streams requiring less decoding energy than conventionally coded bit streams. To this end, we propose extending the standard rate-distortion optimization approach to also consider the decoding energy. In the encoder, the decoding energy is...

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Veröffentlicht in:IEEE transactions on circuits and systems for video technology Jg. 29; H. 1; S. 171 - 182
Hauptverfasser: Herglotz, Christian, Heindel, Andreas, Kaup, Andre
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.01.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Codec
Decoding
decoding energy
Distortion
Encoding
Energy
Energy costs
energy model
Hardware
HEVC
Optimization
Parameters
Random access memory
rate-distortion optimization
Software
Streams
Video compression
ISSN:1051-8215, 1558-2205
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Zusammenfassung:This paper presents a method for generating coded video bit streams requiring less decoding energy than conventionally coded bit streams. To this end, we propose extending the standard rate-distortion optimization approach to also consider the decoding energy. In the encoder, the decoding energy is estimated during runtime using a feature-based energy model. These energy estimates are then used to calculate decoding-energy-rate-distortion costs that are minimized by the encoder. This ultimately leads to optimal tradeoffs between these three parameters. Therefore, we introduce the mathematical theory for describing decoding-energy-rate-distortion optimization and the proposed encoder algorithm is explained in detail. For rate-energy control, a new encoder parameter is introduced. Finally, measurements of the software decoding process for HEVC-coded bit streams are performed. Results show that this approach can lead to up to 30% of decoding energy reduction at a constant visual objective quality when accepting a bit rate increase at the same order of magnitude.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2017.2771819