🤖 AI Summary
This study addresses the temporal inconsistency—such as flickering and motion jerkiness—that commonly arises in video compression at low bitrates, a phenomenon whose relationship with compression intensity remains poorly understood. The authors systematically evaluate the impact of mainstream codecs (AV1, HEVC, VP9, and H.264) on inter-frame consistency across varying bitrates and content types, employing objective metrics to quantify temporal distortion. Their findings reveal that temporal consistency degrades nonlinearly with increasing compression strength and that videos with unpredictable dynamics exhibit greater temporal instability than those with high but predictable motion—challenging the conventional assumption that motion magnitude alone dictates encoding difficulty. These results underscore the urgent need to incorporate temporally aware quality metrics into existing compression pipelines to enhance perceptual visual fidelity.
📝 Abstract
While video compression algorithms effectively reduce bitrate, aggressive quantization often compromises temporal coherence, introducing artifacts such as flicker, motion inconsistency, and unstable textures. Although spatial quality degradation is well-documented, the relationship between compression intensity and temporal stability remains insufficiently characterized. This paper systematically examines the progression of frame-to-frame coherence errors across different bitrate regimes, utilizing multiple codecs (AV1, HEVC, VP9, H.264) and content types. Our findings reveal that temporal consistency degrades non-linearly with increasing compression. Most critically, we identify a "Predictability anomaly" where sequences with unpredictable or irregular dynamics experience disproportionately higher instability than sequences with higher, but more predictable, motion magnitude. This challenges the conventional assumption that motion volume alone dictates encoding difficulty and highlights the necessity of temporal-aware metrics in compression pipelines.