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Electrical Engineering and Systems Science > Image and Video Processing

arXiv:2401.16067 (eess)
[Submitted on 29 Jan 2024 (v1), last revised 30 Jan 2024 (this version, v2)]

Title:Encoding Time and Energy Model for SVT-AV1 based on Video Complexity

Authors:Lena Eichermüller, Gaurang Chaudhari, Ioannis Katsavounidis, Zhijun Lei, Hassene Tmar, Christian Herglotz, André Kaup
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Abstract:The share of online video traffic in global carbon dioxide emissions is growing steadily. To comply with the demand for video media, dedicated compression techniques are continuously optimized, but at the expense of increasingly higher computational demands and thus rising energy consumption at the video encoder side. In order to find the best trade-off between compression and energy consumption, modeling encoding energy for a wide range of encoding parameters is crucial. We propose an encoding time and energy model for SVT-AV1 based on empirical relations between the encoding time and video parameters as well as encoder configurations. Furthermore, we model the influence of video content by established content descriptors such as spatial and temporal information. We then use the predicted encoding time to estimate the required energy demand and achieve a prediction error of 19.6 % for encoding time and 20.9 % for encoding energy.
Comments: 5 pages, 1 figure, accepted for IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2024
Subjects: Image and Video Processing (eess.IV); Multimedia (cs.MM)
Cite as: arXiv:2401.16067 [eess.IV]
  (or arXiv:2401.16067v2 [eess.IV] for this version)
  https://doi.org/10.48550/arXiv.2401.16067

Submission history

From: Lena Eichermüller [view email]
[v1] Mon, 29 Jan 2024 11:22:33 UTC (256 KB)
[v2] Tue, 30 Jan 2024 12:49:06 UTC (257 KB)
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