Adaptive Resolution and Chroma Subsampling for Energy-Efficient Video Coding

TL;DR

The paper introduces ARCS, an adaptive framework that jointly optimizes resolution and chroma subsampling in video encoding to improve energy efficiency and quality, outperforming fixed-format methods.

Contribution

It proposes a novel joint optimization approach for resolution and chroma subsampling, introducing chroma adaptivity as a new control dimension for energy-efficient video streaming.

Findings

13.48% bitrate savings compared to fixed formats

62.18% reduction in decoding time

Maintains perceptual quality with adaptive encoding

Abstract

Conventional video encoders typically employ a fixed chroma subsampling format, such as YUV420, which may not optimally reflect variations in chroma detail across different types of content. This can lead to suboptimal chroma quality and inefficiencies in bitrate allocation. We propose an Adaptive Resolution-Chroma Subsampling (ARCS) framework that jointly optimizes spatial resolution and chroma subsampling to balance perceptual quality and decoding efficiency. ARCS selects an optimal (resolution, chroma format) pair for each bitrate by maximizing a composite quality-complexity objective, while enforcing monotonicity constraints to ensure smooth transitions between representations. Experimental results using x265 show that, compared to a fixed-format encoding (YUV444), on average, ARCS achieves a 13.48 % bitrate savings and a 62.18 % reduction in decoding time, which we use as a proxy for the decoding energy, to yield the same colorVideoVDP score. The proposed framework introduces chroma adaptivity as a new control dimension for energy-efficient video streaming.