Method for condensing training dataset, and image processing device

An image processing device comprising:

• memory storing one or more instructions;
• and
• one or more processors configured to execute the one or more instructions stored in the memory,
• wherein the instructions, when executed by the one or more processors individually or collectively, cause the image processing device to:
• obtain a meta model for processing an input image, the meta model being based on an image quality value of the input image,
• obtain a condensed high-resolution (HR) dataset corresponding to a training dataset,
• obtain a degraded dataset corresponding to the condensed HR dataset, the degraded dataset being based on the input image,
• training the meta model based on the condensed HR dataset and the degraded dataset, and
• output an image-quality processed output image having a higher quality than the input image using the trained meta model.

An electronic device configured to condense a training dataset for image processing, the electronic device comprising:

• memory storing one or more instructions;
• and
• one or more processors configured to execute the one or more instructions stored in the memory,
• wherein the instructions, when executed by the one or more processors individually or collectively, cause the electronic device to:
• generate a training dataset using a plurality of images, wherein the plurality of images are images have contrast information satisfying a predefined condition;
• generate a cluster set comprising a plurality of clusters based on clustering the training dataset;
• generate an initial condensed high-resolution (HR) dataset by selecting, for each cluster included in the cluster set, one or more images from among a respective cluster in the training dataset;
• obtain a first loss of a first neural network model based on the training dataset and obtain a second loss of a second neural network model based on the initial condensed HR dataset;
• generate a condensed HR dataset by updating, based on the first loss and the second loss, pixels in each of the one or more images included in each cluster of the initial condensed HR dataset;
• and
• transmit the condensed HR dataset to an image processing device.