Optimizing Video Coding Using a Deep Learning Model

A non-transitory, computer-readable medium storing a set of instructions for optimizing encoding of video frames, that, when executed by a processor, cause:

• receiving a video frame to be encoded;
• using one or more machine learning models:
• generating an encoding parameter value for encoding the video frame;
• comparing a first set of delta encoding values, based on the encoding parameter value, representing differences between groups of pixels of the video frame to a second set of delta encoding values, based on an alternative encoding parameter value, representing differences between the groups of pixels of the video frame;
• in response to determining that the first set of delta encoding values is less than the second set of delta encoding values, selecting the encoding parameter value;
• and
• based on the encoding parameter value, encoding the video frame to generate an encoded video frame.

A network-based system for optimizing encoding of video frames, the system comprising:

• a processor;
• a memory operatively connected to the processor and storing instructions that, when executed by the processor, cause:
• receiving a video frame to be encoded;
• using one or more machine learning models:
• generating an encoding parameter value for encoding the video frame;
• comparing a first set of delta encoding values, based on the encoding parameter value, representing differences between groups of pixels of the video frame to a second set of delta encoding values, based on an alternative encoding parameter value, representing differences between the groups of pixels of the video frame;
• in response to determining that the first set of delta encoding values is less than the second set of delta encoding values, selecting the encoding parameter value;
• and
• based on the encoding parameter value, encoding the video frame to generate an encoded video frame.