Method, electronic device, and storage medium for processing image by using convolution neural network

An electronic device configured to process an image comprising:

• a memory configured to store one or more instructions;
• and
• at least one processor configured to execute the one or more instructions stored in the memory to:
• generate an upscaled image by upscaling an input image;
• obtain a first feature map and a second feature map by inputting the upscaled image to a convolutional neural network and performing a convolution operation on the upscaled image with one or more kernels included in the convolutional neural network;
• obtain a gain map by inputting the first feature map to a first convolutional layer;
• obtain an offset map by inputting the second feature map to a second convolutional layer;
• and
• generate an output image, based on the upscaled image, the gain map, and the offset map,
• wherein the convolutional neural network is configured to be trained to reduce a difference between a hue of the input image and a hue of the output image.

A non-transitory computer-readable recording medium storing a program for executing a method on a computer, the method comprising:

• upscaling an input image to generate an upscaled image;
• obtaining a first feature map and a second feature map by inputting the upscaled image to a convolutional neural network and performing a convolution operation on the upscaled image with one or more kernels included in the convolutional neural network;
• obtaining a gain map by inputting the first feature map to a first convolutional layer;
• obtaining an offset map by inputting the second feature map to a second convolutional layer;
• and
• generating an output image, based on the upscaled image, the gain map, and the offset map,
• wherein the convolutional neural network is configured to be trained to reduce a difference between a hue of the input image and a hue of the output image.