Method and device for improving image quality on basis of super-resolution neural network

A image quality enhancement method optimized for distortion characteristics of a target image, the image quality enhancement method comprising:

• training, by using training datasets with different distortions, one or more super-resolution neural networks (SRNs) to be respectively optimized for a certain distortion;
• computing, by using a degradation encoder neural network (DEN), a similarity between a service dataset and each of the training datasets that are applied respectively to the one or more super-resolution neural networks;
• selecting, among the one or more super-resolution neural networks, a super-resolution neural network trained with a training dataset having a highest similarity;
• and
• converting the target image into a high-quality image by using the selected super-resolution neural network.

A image quality enhancement device optimized for distortion characteristics of a target image, the image quality enhancement device comprising:

• a memory configured to store one or more instructions;
• and
• a processor,
• wherein the processor is configured to execute the one or more instructions for performing the steps of:
• training, by using training datasets with different distortions, one or more super-resolution neural networks (SRNs) to be respectively optimized for a certain distortion;
• computing, by using a degradation encoder neural network (DEN), a similarity between a service dataset and each of the training datasets that are applied respectively to the one or more super-resolution neural networks;
• selecting, among the one or more super-resolution neural networks, a super-resolution neural network trained with a training dataset having a highest similarity;
• and
• converting the target image into a high-quality image by using the selected super-resolution neural network.