Apparatus, method, and computer-readable medium for image processing, and system for training a neural network

A method of training a generative adversarial network, the method comprising:

• iteratively enhancing a first noise input having a first amplitude and a first reference image in a generative network to generate a first output image,
• iteratively enhancing a second noise input having a second amplitude and the first reference image in the generative network to generate a second output image,
• transmitting the first output image and a second reference image to a discriminative network, the second reference image corresponding to the first reference image and having a higher resolution than the first reference image,
• obtaining a first score from the discriminative network based on the second reference image, and a second score from the discriminative network based on the first output image,
• calculating a loss function of the generative network based on the first score and the second score, and
• adjusting at least one parameter of the generative network to lower the loss function of the generative network.