A Bit Stream Feature-Based Energy Estimator for HEVC Software Encoding

TL;DR

This paper introduces a bit stream feature-based model that accurately estimates the energy consumption of HEVC software encoding, aiding the development of energy-efficient video coding algorithms.

Contribution

It presents a novel energy estimator using bit stream features that achieves high accuracy, reducing the need for costly energy measurements.

Findings

Mean estimation error of 4.88% across presets

Identifies properties of energy-efficient bit streams

Supports development of energy-saving video coding algorithms

Abstract

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 4.88% 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.