Interra Systems provides end-to-end quality assurance solutions for media professionals, streamlining content preparation and delivery across IP and OTT workflows. Their award-winning products include BATON automated QC system, BATON Captions solution, ORION content monitoring platforms, and VEGA Media Analyzer.
Interra Systems has integrated Netflix’s VMAF algorithm into its VEGA Media Analyzer, enhancing video quality assessment with perceptual accuracy and efficiency for media companies, broadcasters, and streaming services.
The integration of VMAF into VEGA Media Analyzer is crucial because it enables media companies to deliver high-quality, viewer-centric video experiences. It provides perceptually accurate quality assessments, automates quality control processes, and optimizes encoding decisions for better quality-to-bitrate ratios. This ensures efficient streaming, reduced artifacts, and enhanced audience satisfaction in competitive OTT environments.
Interra Systems, a leading provider of end-to-end quality assurance solutions for the digital media industry, today announced the integration of Netflix’s Video Multi-method Assessment Fusion (VMAF) algorithm — a widely-trusted standard for video quality assessment — into its industry-leading VEGA Media Analyzer solution. This integration empowers media companies, broadcasters, and streaming services to assess video quality with increased precision and efficiency, meeting the growing demand for perceptually accurate quality control (QC) across high-stakes streaming environments.
Developed by Netflix, VMAF has become a benchmark for perceptual video quality assessment, offering reliable measurements of video quality as experienced by viewers. Combining this with VEGA’s in-depth video analysis provides users with a powerful platform for evaluating and optimizing video quality, ensuring seamless and engaging streaming experiences for audiences worldwide.
“VEGA has long been an essential tool for ensuring that encoded streams are standards-compliant and interoperable with industry-standard players. Adding VMAF quality checks incorporates a highly valuable component, as VMAF has demonstrated the highest correlation with human Mean Opinion Score (MOS) comparisons, making it the most accurate metric for assessing subjective quality. It’s a metric I rely on daily in my consulting, training, and writing practices,” said Jan Ozer, streaming learning center and contributing editor to Streaming Media Magazine.
Adding VMAF support to VEGA Media Analyzer offers significant benefits for media companies, broadcasters, and service providers, including enhanced perceptual accuracy, efficient quality control, and optimized streaming performance. VMAF scoring captures video quality as perceived by the human eye, ensuring that quality assessments are viewer-centric. This integration also automates quality assessments, enabling faster and more consistent results across a wide range of content. VMAF scores guide encoding and bitrate decisions, helping achieve the best quality-to-bitrate ratio and improving overall streaming efficiency.
“Today, media companies face the critical challenge of delivering high-quality video across a range of resolutions to meet diverse OTT streaming demands,” said Anupama Anantharaman, vice president of product management at Interra Systems. “By integrating VMAF into VEGA Media Analyzer, we enable encoder and transcoder developers to assess video quality more efficiently. This integration provides actionable insights for encoding decisions that enhance viewer experience while maintaining operational efficiency.”
Anantharaman added, “For streaming companies, delivering high-quality video is paramount. With this integration, they now have access to industry-standard quality benchmarks, allowing video engineers to optimize compression, reduce artifacts, and provide a viewing experience that meets the highest quality standards.”
With VMAF now built into VEGA Media Analyzer, Interra Systems reaffirms its commitment to delivering best-in-class tools that meet the evolving needs of the video streaming industry. This integration allows video quality engineers and media professionals to make data-driven, perceptually accurate quality decisions that resonate with audiences.
