Image processing method, image processing apparatus, image processing system, image pickup apparatus, learning method, learning apparatus, and memory

An image processing apparatus comprising:

• a processor configured to:
• generate a first image by inputting an input image or an image based on the input image into a first machine learning model;
• generate a second image by inputting the first image into a second machine learning model different from the first machine learning model;
• and
• generate a third image by using the first image and the second image,
• wherein each of the first image, the second image, and the third image has a larger number of pixels than those of the input image, and
• wherein the second image has fewer high-frequency components than those of the first image.

A method of training a machine learning model comprising:

• acquiring a first training image having a low resolution or an image based on the first training image, and a second training image having a high resolution corresponding to the first training image;
• and
• training a first machine learning model and a second machine learning model based on the first training image or the image based on the first training image and the second training image,
• wherein a calculating method of a loss during training of the first machine learning model and a training method of a loss during learning of the second machine learning model are different from each other.

A learning apparatus comprising:

• a processor configured to:
• acquire a first training image having a low resolution or an image based on the first training image, and a second training image having a high resolution corresponding to the first training image;
• and
• train a first machine learning model and a second machine learning model based on the first training image or the image based on the first training image and the second training image,
• wherein a calculating method of a loss during learning of the first machine learning model and a calculating method of a loss during learning of the second machine learning model are different from each other.