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Decoding-Energy-Rate-Distortion Optimization for Video Coding

Bibliographic Details
Journal Title: IEEE Transactions on Circuits and Systems for Video Technology
Authors and Corporations: Herglotz, Christian, Heindel, Andreas, Kaup, Andre
In: IEEE Transactions on Circuits and Systems for Video Technology, 29, 2019, 1, p. 171-182
Media Type: E-Article
Language: English
published:
IEEE
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rft.atitle Decoding-Energy-Rate-Distortion Optimization for Video Coding
rft.epage 182
rft.issn 1051-8215
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rft.jtitle IEEE Transactions on Circuits and Systems for Video Technology
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rft.date 2019-01-01
x.date 2019-01-01T00:00:00Z
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abstract 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.
authors Array ( [rft.aulast] => Herglotz [rft.aufirst] => Christian )
Array ( [rft.aulast] => Heindel [rft.aufirst] => Andreas )
Array ( [rft.aulast] => Kaup [rft.aufirst] => Andre )
doi 10.1109/TCSVT.2017.2771819
languages eng
url http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8103054
http://doi.org/10.1109/TCSVT.2017.2771819
version 0.9
x.subjects Decoding
Encoding
Software
Optimization
Standards
Hardware
Random access memory
Codec
decoding energy
rate-distortion optimization
energy model
HEVC
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IEEE Transaction
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author Herglotz, Christian, Heindel, Andreas, Kaup, Andre
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description 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.
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spelling Herglotz, Christian Heindel, Andreas Kaup, Andre 1051-8215 IEEE Decoding Encoding Software Optimization Standards Hardware Random access memory Codec decoding energy rate-distortion optimization energy model HEVC http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8103054 http://doi.org/10.1109/TCSVT.2017.2771819 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. Decoding-Energy-Rate-Distortion Optimization for Video Coding IEEE Transactions on Circuits and Systems for Video Technology
spellingShingle Herglotz, Christian, Heindel, Andreas, Kaup, Andre, IEEE Transactions on Circuits and Systems for Video Technology, Decoding-Energy-Rate-Distortion Optimization for Video Coding, Decoding, Encoding, Software, Optimization, Standards, Hardware, Random access memory, Codec, decoding energy, rate-distortion optimization, energy model, HEVC
title Decoding-Energy-Rate-Distortion Optimization for Video Coding
title_full Decoding-Energy-Rate-Distortion Optimization for Video Coding
title_fullStr Decoding-Energy-Rate-Distortion Optimization for Video Coding
title_full_unstemmed Decoding-Energy-Rate-Distortion Optimization for Video Coding
title_short Decoding-Energy-Rate-Distortion Optimization for Video Coding
title_sort decoding-energy-rate-distortion optimization for video coding
topic Decoding, Encoding, Software, Optimization, Standards, Hardware, Random access memory, Codec, decoding energy, rate-distortion optimization, energy model, HEVC
url http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8103054, http://doi.org/10.1109/TCSVT.2017.2771819