Microsoft patents ML video compression that boosts quality
This patent describes a system that uses machine learning to improve how video is compressed and played back. It works by having an AI network adjust the video before it is saved and another AI network fix up the video after it is loaded, which helps remove blurry spots and other quality issues caused by compression.
In the filing’s own words
Innovations in machine learning (“ML”) networks used in video processing scenarios are described. For example, an ML refinement network can be used to refine video after a video decoder has reconstructed the video. Using the ML refinement network for post-processing can mitigate compression artifacts introduced during encoding and otherwise improve the quality of the reconstructed video. Or, as another example, an ML encoder network and ML decoder network can be used, in combination with a core video encoder and core video decoder, for hybrid compression and corresponding decompression. In the hybrid compression, the ML encoder network can transform video before encoding in order to boost rate-distortion performance of the core video encoder. In corresponding decompression, the ML decoder network can enhance reconstructed video after decoding, thereby compensating for transformations applied by the ML encoder network, mitigating compression artifacts, and otherwise improving the quality of the reconstructed video.
What exactly they claim (claim 1)
1. A server computer system comprising a processor system and memory, wherein the server computer system is configured to perform operations comprising: receiving a current unit of input video; retrieving a given previous unit; warping the given previous unit to spatially align sample values of the given previous unit with expected locations in a version of the current unit, thereby producing a given warped previous unit; providing the given warped previous unit to a machine learning (“ML”) encoder network; with the ML encoder network, transforming the current unit to facilitate preservation of image quality, thereby producing a transformed current unit, wherein, as part of a temporal feedback loop, the transforming the current unit is based at least in part on the given warped previous unit; encoding the transformed current unit, thereby producing encoded data for the transformed current unit; and outputting the encoded data as part of a bitstream.
Facts
- Company
- Microsoft (Microsoft Technology Licensing, LLC)
- Official title
- Machine learning networks for hybrid video compression and corresponding decompression
- Patent number
- US12744944B2
- Application number
- 18680485
- Filed
- May 31, 2024
- Granted
- Sep 22, 2026
- Inventors
- 3
- Claims
- 20
Classified under
H04N 19/86 Electricity & electronicsH04N 19/132 Electricity & electronicsH04N 19/423 Electricity & electronicsH04N 19/60 Electricity & electronicsH04N 19/172 Electricity & electronicsH04N 19/174 Electricity & electronicsMore from Microsoft in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.