Machine learning algorithm using compression parameter for image reconstruction and image reconstruction method therewith

摘要

The present invention uses compressed information and a degraded image as input data, and is configured to learn and derive an optimal model corresponding to various compressed information by using a machine learning algorithm aiming to restore the original image. It is possible to remarkably improve the image resilience and compression rate by applying the optimal model corresponding to the information, and to construct the loss function which is a function for calculating the difference between the reconstructed image and the original image during learning. The present invention provides a machine learning algorithm capable of precisely restoring an image for a specific region by assigning a weight and an image restoration method using the same.