Energy-Aware Frame Rate Selection for Video Coding
Ramasubbu G, Kaup A, Herglotz C (2026)
Publication Type: Journal article, Original article
Publication year: 2026
Journal
DOI: 10.1109/ACCESS.2026.3672053
Open Access Link: https://ieeexplore.ieee.org/document/11424564
Abstract
The demand for high-quality, immersive video experiences has necessitated adopting higher frame rates for more realistic scene portrayal. However, there is a growing demand for energy-saving video applications, where temporal downsampling is a crucial energy-saving factor. To this end, the main contributions of this paper are twofold: First, we present an in-depth analysis of the impact of frame rate reductions on the visual quality of the video and the encoding as well as decoding energy. Second, we propose a lightweight frame rate selection method for energy- and quality-aware encoding. Concerning the first contribution, this paper performs extensive encoding and decoding measurements, followed by an investigation of the impact of temporal downsampling on the energy demand of encoding and decoding at different frame rates. Furthermore, we determine the objective visual quality of the downsampled videos. As a result of this investigation, we identify content- and quantization-setting-dependent energy-aware frame rates, i.e., the temporal downsampling factors that lead to Pareto-optimality in terms of energy and quality. We demonstrate that significant energy savings are achieved while maintaining constant visual quality. Subsequently, a subjective experiment is conducted to verify this observation regarding perceptual quality using mean opinion scores. As the second contribution, we propose an energy-aware frame rate selection method that extracts spatio-temporal features from the video sequences. Based on these features, the proposed method employs a feature-based supervised machine learning approach to predict energy-aware frame rates for a given quantization parameter and video sequence, aiming to reduce energy consumption during encoding and decoding. The experimental results demonstrate that the proposed method offers significant energy savings, with an average of 17.46% and 17.60% of encoding and decoding energy demand reduction, respectively, alongside 3.38% average bitrate savings at a constant quality.
Authors with CRIS profile
Geetha Ramasubbu
Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS)
Andre Kaup
Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS)
Involved external institutions
Germany (DE)How to cite
APA:
Ramasubbu, G., Kaup, A., & Herglotz, C. (2026). Energy-Aware Frame Rate Selection for Video Coding. IEEE Access. https://doi.org/10.1109/ACCESS.2026.3672053
MLA:
Ramasubbu, Geetha, André Kaup, and Christian Herglotz. "Energy-Aware Frame Rate Selection for Video Coding." IEEE Access (2026).
BibTeX: Download