Accurate and proven AI enhancement model for rapid reconstruction of high-definition video.
Resolution reconstruction, color enhancement, denoising, artifacts removal, etc. six major functions of lightweight decoupling, ready to mix and match.
With a pre-picture quality discriminator, intelligently identifying the video quality with adaptive processing, and reduce the amount of manual tasks.
Based on the AI super-resolution model, the local missing information in low-definition images can be accurately restored to achieve 2 or 3 times of super-resolution.
Through processing techniques such as artifact removal, noise reduction, sharpening and high frame rate reset, the noise, burr, artifact, blurry mosaic and jitter in the video can be effectively eliminated, at the same time, the smoothness of the video can be improved and user frustration can be reduced.
By identifying the video type and graphic content, the best parameters are intelligently selected according to the human vision model, and the bitrate is dynamically adapted.
Adaptive adjustment of color, brightness, contrast, saturation and other aspects in the image can significantly improve the visual effect of the video.
The quality of the short videos uploaded by users can be unpredictable, and there are many noises and blurred images. For manual identification of video quality, the labor cost is extremely high:
Old movies, TV dramas and documentaries have been stored for a long time, and after the film is converted into digital formats, it often produce noise, scratches, gray colors and other phenomena, which can not meet the standard of large screen HD:
The 4K format of radio and television is a special case, which shall meet the requirements of BT.2020 color gamut, 50p high frame rate and 10 bit depth all at the same time. Using intranet transmission, it is difficult to access the video repair technology on the public network and cannot meet the broadcasting standards of high-definition channels: