Ramasubbu G, Kaup A, Herglotz C (2022)
Publication Language: English
Publication Type: Conference contribution
Publication year: 2022
Event location: San Jose, California
URI: https://arxiv.org/abs/2212.05609
DOI: 10.1109/PCS56426.2022.10018048
The total energy consumption of today's video coding systems is globally significant and emphasizes the need for sustainable video coder applications. To develop such sustainable video coders, the knowledge of the energy consumption of state-of-the-art video coders is necessary. For that purpose, we need a dedicated setup that measures the energy of the encoding and decoding system. However, such measurements are costly and laborious. To this end, this paper presents an energy estimator that uses a subset of bit stream features to accurately estimate the energy consumption of the HEVC software encoding process. The proposed model reaches a mean estimation error of 4.88video coding, energy-efficiency, energy estimator, HEVC, bit stream features% when averaged over presets of the x265 encoder implementation. The results from this work help to identify properties of encoding energy-saving bit streams and, in turn, are useful for developing new energy-efficient video coding algorithms.
APA:
Ramasubbu, G., Kaup, A., & Herglotz, C. (2022). A Bit Stream Feature-Based Energy Estimator for HEVC Software Encoding. In Proceedings of the Picture Coding Symposium (PCS 2022). San Jose, California.
MLA:
Ramasubbu, Geetha, André Kaup, and Christian Herglotz. "A Bit Stream Feature-Based Energy Estimator for HEVC Software Encoding." Proceedings of the Picture Coding Symposium (PCS 2022), San Jose, California 2022.
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