iSize Develops AI-Based ‘Precoder’
A pixel-to-pixel neural-network solution.
iSize Technologies’ BitSave v.2 is described as a pixel-to-pixel neural-network solution that optimizes video frames before the pixels reach the video compression software.
This ‘precoder’ is said to enhance details of the areas of each frame that affect the perceptual quality score of the content after encoding and attenuates details that are not important.
This, says iSize, is designed to optimally balance perceptual quality against encoding bitrate. The solution is data-driven, trained on large image and video datasets, with no hand-crafted parameters.
It incurs a single-frame latency, can be used with any third-party video encoder with no changes in the encoding pipeline, and can run in real-time for up to 4K resolution.
iSize Technologies CEO Sergio Grce said, “It is predicted that by the end of 2020, more than 82% of internet traffic will be taken up by video, with consumers increasingly investing in and consuming higher quality video content. In response to this fast-moving market, iSize develops innovative codec independent software solutions that allows data-heavy video content to be compressed to a fraction of its original size, meaning content can be streamed faster and at a better quality.”
Extensive testing has shown its patent-pending AI features can make encoding up to 500% faster.
Since BitSave can be used alongside existing software, companies that have invested in compression software can use BitSave as an ‘add-on’ without having to shelve ongoing projects. The AI technology behind BitSave is fully codec independent, increasing the efficiency and performance of all the latest codec standards including AVC/H.264, HEVC/H.265, and VP9. This ensures seamless integration with existing media workflows.
BitSave is also unconstrained by standards because it produces a pixel output, which means it can use neural networks and add multiple quality functions that cannot be achieved otherwise.
“Ultimately, BitSave allows consumers to stream higher quality video, using less data or bandwidth, thus reducing the environmental impact of streaming. The devices used will also need to use less computing power to stream quality video, which means a longer battery life when watching content on the go,” says Grce.
You might also like...
Compression: Part 12 - The Evolution Of Video Compression
Having considered all of the vital elements of moving image coding this final part looks at how these elements were combined throughout coding history.
Understanding The Client-Side OTT Customer Experience
The criticality of service assurance in OTT services is evolving quickly as audiences grow and large broadcasters double-down on their streaming strategies.
Motion Pictures: Part 5 - True Motion TV
Having looked at the traditional approach to moving pictures and found that the portrayal of motion was irremediably poor, thoughts turn to how moving pictures might be portrayed properly.
The Potential Impact Of Quantum Computing
Quantum Computing is still a developmental technology but it has the potential to completely transform more or less everything we currently assume regarding what computers can and can’t do - when it hits the mainstream what will it do…
OTT Monitoring From The Network Side
At its core, the network-side can be an early warning system for QoS, which in turn correlates to actual QoE performance.