Decoding Energy Modeling For Versatile Video Coding

TL;DR

This paper introduces two new bit stream feature-based energy models for VVC, demonstrating comparable accuracy to existing HEVC models with an estimation error of 1.85%, aiding energy-efficient video decoding.

Contribution

The paper presents novel energy modeling approaches specifically tailored for VVC, extending prior HEVC models with comparable accuracy.

Findings

Models achieve 1.85% mean estimation error

Comparable accuracy to existing HEVC models

Effective for energy-efficient VVC decoding

Abstract

In previous research, it was shown that the software decoding energy demand of High Efficiency Video Coding (HEVC) can be reduced by 15$\%$ by using a decoding-energy-rate-distortion optimization algorithm. To achieve this, the energy demand of the decoder has to be modeled by a bit stream feature-based model with sufficiently high accuracy. Therefore, we propose two bit stream feature-based models for the upcoming Versatile Video Coding (VVC) standard. The newly introduced models are compared with models from literature, which are used for HEVC. An evaluation of the proposed models reveals that the mean estimation error is similar to the results of the literature and yields an estimation error of 1.85% with 10-fold cross-validation.