VisualOn&The Channel Store Show Up to 65% Bitrate Savings with AI-Driven Content-Adaptive Encoding
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Independent analysis confirms faster encoding, lower CPU usage, and improved perceptual quality compared to CBR and CRF

CUPERTINO, Calif. - Californer -- 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.

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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: 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:

👉 Read the whitepaper https://www.visualon.com/index.php/latest-news/visualon-optimizer-content-adaptive-encoding-vs-cbr-and-crf/

Contact
Savi Shi
***@visualon.com


Source: VisualOn

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