Independent analysis confirms faster encoding, lower CPU usage, and improved perceptual quality compared to CBR and CRF
VisualOn, a leader in multimedia playback and video optimization technologies, today announced the publication of a new whitepaper featuring results from an independent evaluation conducted by The Channel Store (TCS), part of the TVUP Media Group, a leading provider of cloud-based playout and OTT distribution solutions, delivering linear and on-demand content for broadcasters across Europe and Latin America.
In the study, TCS evaluated VisualOn’s AI-driven Optimizer against traditional CBR and CRF encoding methods in production-grade VOD workflows, confirming up to 65% average bitrate savings while maintaining or improving perceptual video quality. The study was conducted using H264 software encoding with FFmpeg.
The whitepaper, “Content-Adaptive Encoding: VisualOn Optimizer vs. CBR and CRF,” presents a comprehensive comparison of CBR, Constant Rate Factor (CRF), and VisualOn Optimizer, based on an independent evaluation conducted by The Channel Store (TCS) across a wide range of real-world content, including sports, news, film, series, and animation. Tests were conducted in TCS production-like VOD workflows using industry-standard tools and objective quality metrics such as VMAF.
Key findings from the evaluation include:
- Substantial bitrate reduction: Existing CRF profiles achieve 34% bitrate savings across resolutions (1080p, 720p, 480p) compared to CBR profiles, while VisualOn Optimizer improves this to as much as 65% savings.
- Maintained or improved visual quality: VMAF scores remained stable or improved by 1–3 points across all tested content categories.
- Performance improvements: VisualOn Optimizer delivered 7–27% faster encoding times than CBR and reduced CPU usage by up to 50%, including 28% lower CPU consumption compared to the current CRF baseline, thus enabling more efficient large-scale deployments.
- Broad content adaptability: Particularly strong gains were observed in animation, sports, and news content, demonstrating the effectiveness of AI-driven, content-adaptive perceptual optimization.
The evaluation highlights VisualOn Optimizer’s seamless integration into existing FFmpeg-based workflows, enabling operators to quickly adopt advanced optimization techniques with minimal operational disruption.
The full whitepaper is now available for download:
