Processing method and system for convolutional neural network, and storage medium

A processing method for a convolutional neural network, comprising training a generator and training a discriminator, wherein training a generator comprises:

• extracting a low-resolution color image from a high-resolution color image;
• training parameters of a generator network, by using the low-resolution color image and a noise image as an input image, based on parameters of a discriminator network, and reducing a generator cost function, wherein,
• the generator network includes a lifting layer for lifting resolutions of a luminance component and a chrominance component of the input image;
• the generator cost function represents a degree of difference between an output image of the generator network and the high-resolution color image;
• training a discriminator comprises:
• inputting the output image of the trained generator network and the high-resolution color image to the discriminator network, respectively;
• training parameters of the discriminator network by reducing a discriminator cost function, wherein,
• the discriminator network includes a pooling layer for reducing resolution;
• the discriminator cost function represents a degree in which the output image of the generator network corresponds to the high-resolution color image.