Energy-Aware Frame Rate Selection for Video Coding

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Ramasubbu, Geetha, Kaup, Andrè, Herglotz, Christian
Format: Preprint
Published: 2026
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866910059091460096
author Ramasubbu, Geetha
Kaup, Andrè
Herglotz, Christian
author_facet Ramasubbu, Geetha
Kaup, Andrè
Herglotz, Christian
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2603_18305
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Energy-Aware Frame Rate Selection for Video Coding
Ramasubbu, Geetha
Kaup, Andrè
Herglotz, Christian
Image and Video Processing
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.
title Energy-Aware Frame Rate Selection for Video Coding
topic Image and Video Processing
url https://arxiv.org/abs/2603.18305