Generation of low-high quality data pairs for training a denoising model

A system comprising:

• a communications interface;
• a non-transitory computer-readable medium;
• and
• one or more processors communicatively coupled to the communications interface and the non-transitory computer-readable medium, the one or more processors configured to execute processor-executable instructions stored in the non-transitory computer-readable medium to:
• access a first set of video data with a first noise level above a first threshold value;
• extract a noise sequence from the first set of video data;
• augment one or more noise frames of the noise sequence in one or more aspects to obtain one or more augmented noise frames;
• and
• apply the one or more augmented noise frames to a second set of video data with a second noise level below a second threshold value to generate a third set of video data;
• generate a pair of training video data comprising the second set of video data and the third set of video data;
• and
• train a machine learning model using the pair of training video data to denoise video data.

A non-transitory computer-readable medium comprising processor-executable instructions configured to cause one or more processors to:

• access a first set of video data with a first noise level above a first threshold value;
• extract a noise sequence from the first set of video data;
• augment one or more noise frames of the noise sequence in one or more aspects to obtain one or more augmented noise frames;
• and
• apply the one or more augmented noise frames to a second set of video data with a second noise level below a second threshold value to generate a third set of video data;
• generate a pair of training video data comprising the second set of video data and the third set of video data;
• and
• train a machine learning model using the pair of training video data to denoise video data.