Deep learning-based quality control of video compression

A system for real-time quality control of video compression for streaming media, comprising:

• a memory device;
• one or more processor devices operatively coupled with the memory device to:
• partition video data from the streaming media into video chunks;
• encode the video chunks with respective quantization parameters (QP);
• predict an optimized QP from the video chunks and their respective QP that conforms to a peak signal-to-noise ratio (PSNR) threshold while minimizing an encoded video bitrate of the compressed video by utilizing a trained video quality control unit (VQCU);
• and
• update the video quality of a streaming media with the optimized QP.

A non-transitory computer program product comprising a computer-readable storage medium including program code for deep learning-based quality control for video compression, wherein the program code when executed on a computer causes the computer to:

• partition video data from streaming media into video chunks;
• encode the video chunks with respective quantization parameters (QP);
• predict an optimized QP from the video chunks and their respective QP that conforms to a peak signal-to-noise ratio (PSNR) threshold while minimizing an encoded video bitrate of the compressed video by utilizing a trained video quality control unit (VQCU);
• and
• update the video quality of a streaming media with the optimized QP.