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← Encoding & Software
EncodingTechnical DevelopmentJuly 11, 2026

Optimizing AV1 Benchmarks Through High-Chaos and Film Grain Test Scenes

Optimizing AV1 Benchmarks Through High-Chaos and Film Grain Test Scenes
YouTube

The Fiction Method released technical guidelines for selecting test clips to benchmark video encoders, focusing on the use of high-chaos scenes and calm dialogues. The analysis identifies AV1's tendency to create block-pattern artifacts on flat, grainy surfaces, noting that encoders require specific tuning to preserve visual quality at reasonable bitrates.

Key Takeaways

  • Test clips should include 'worst-case' chaotic elements like rain, snow, or underwater bubbles to push bitrate limits.
  • Calm dialogue scenes are required to establish a baseline for temporal inter-frame compression efficiency.
  • AV1 demonstrates a specific tendency to create 'patchwork' block artifacts on flat, grainy surfaces like skies and walls.
  • Encoding scripts leverage FFmpeg, MKVToolNix, and Upscayl for generating and processing benchmarking assets.
  • Preserving film grain in AV1 often mandates manual tuning to prevent the encoder from crushing noisy blocks into single-color patterns.

Why It Matters

Accurate codec benchmarking is critical as providers transition away from HEVC toward royalty-free alternatives like AV1. The identified artifact risks suggest that standard automated metrics may miss 'patchwork' grain errors that distract viewers. As AV1 gains adoption for high-resolution HDR content, engineers must shift from generic presets to scene-aware tuning that prioritizes texture preservation. Watch for the emergence of 'film grain synthesis' as a mandatory decoder feature to mitigate these bitrate-heavy noise artifacts.

Additional Context

The technical challenge of preserving film grain in AV1 is a known industry hurdle, often addressed through Film Grain Synthesis (FGS). Per the Netflix Tech Blog (July 2025), FGS models grain through an auto-regressive (AR) process, allowing for average bitrate reductions of 31.6% by removing noise at the encoder and recreating it at the decoder. This method effectively masks compression artifacts that otherwise appear as discrete cosine transform (DCT)-like patterns in areas of flat color. Current hardware updates, including Apple’s M3+ and NVIDIA’s RTX 40-series, now support native AV1 encoding, further incentivizing these granular optimization techniques. In concurrent benchmarking efforts (March 2026), SVT-AV1 has emerged as a performance leader, reportedly using 9 to 100 times less energy than libaom while maintaining high VMAF scores. However, independent testing on platforms like Reddit (July 2026) continues to highlight issues with macroblocking in dark scenes when default denoising and grain settings are used. Experts recommend disabling default smoothing and using custom variance boost strings to prevent the 'flattening' effects documented by The Fiction Method. According to recent IEEE Transactions on Broadcasting reports (2026), these modeling algorithms are increasingly vital for HDR distribution, where artistic grain intent must be balanced against the 30-50% smaller file sizes AV1 promises over legacy H.264 formats.


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