Decoding-Energy-Rate-Distortion Optimization for Video Coding

TL;DR

This paper introduces a decoding-energy-aware rate-distortion optimization method for video coding, significantly reducing decoding energy consumption while maintaining visual quality by balancing bitrate, energy, and distortion.

Contribution

It extends standard rate-distortion optimization to include decoding energy, proposing a new encoder algorithm and mathematical framework for energy-efficient video coding.

Findings

Up to 30% decoding energy reduction at constant quality

Energy-aware optimization introduces a new encoder parameter

Trade-offs between bitrate, energy, and distortion are effectively managed

Abstract

This paper presents a method for generating coded video bit streams requiring less decoding energy than conventionally coded bit streams. To this end, we propose extending the standard rate-distortion optimization approach to also consider the decoding energy. In the encoder, the decoding energy is estimated during runtime using a feature-based energy model. These energy estimates are then used to calculate decoding-energy-rate-distortion costs that are minimized by the encoder. This ultimately leads to optimal trade-offs between these three parameters. Therefore, we introduce the mathematical theory for describing decoding-energy-rate-distortion optimization and the proposed encoder algorithm is explained in detail. For rate-energy control, a new encoder parameter is introduced. Finally, measurements of the software decoding process for HEVC-coded bit streams are performed. Results show that this approach can lead to up to 30% of decoding energy reduction at a constant visual objective quality when accepting a bitrate increase at the same order of magnitude.