Metrics help compare encodes, but no single score understands every texture, viewing condition, or business need. Answering this compression & quality question well means looking at evidence from the source file, the properties covered below, and what the final destination actually requires.
Compression decisions should compare perceptual quality, structural fidelity, decode support, and transfer cost - Not size alone. In “PSNR, SSIM, and VMAF: what quality scores miss,” begin with this specific observation: PSNR measures signal error and often disagrees with perception.
Three findings that guide this choice
The core distinction
PSNR measures signal error and often disagrees with perception.
The practical trade-off
SSIM models structural similarity.
The verification test
VMAF combines features trained against subjective viewing data.
A practical decision for this workflow
Use metrics to narrow candidates, then review representative scenes on target devices.
Use vmaf combines features trained against subjective viewing data. as the acceptance test on a representative source before committing an entire archive, publication, or delivery batch.
The compression & quality mistake to avoid here
Declaring one encode universally better because its aggregate score is a fraction higher.
That failure conflicts directly with the recommendation for “PSNR, SSIM, and VMAF: what quality scores miss”: Use metrics to narrow candidates, then review representative scenes on target devices.
Review checklist before delivery
- ✓The result meets the actual transfer or storage budget.
- ✓Artifacts are checked in the hardest visual or audible passage.
- ✓Dimensions, duration, and structure were not reduced accidentally.
- ✓The uncompressed or highest-quality master remains available.
The real bar for “PSNR, SSIM, and VMAF: what quality scores miss” is passing these topic-specific checks - a file that simply opens is not enough.