METHOD FOR SINGLE IMAGE DEHAZING BASED ON DEEP LEARNING, RECORDING MEDIUM AND DEVICE FOR PERFORMING THE METHOD

摘要

A deep learning-based image fog removal method includes: when a fog image is input, performing a convolution operation to extract image features; extracting n scaled image features by performing n (where n is a natural number) dilated convolution operations on the extracted image features at different rates; continuously performing a cumulative convolution operation in which the n scale image features are reflected as a cumulative input of the subsequent convolution operation through a plurality of residual dense blocks (RDBs); matching the n scaled image features on which the cumulative convolution operation is continuously performed with the same channel as the fog image; and outputting an image from which fog is removed by comparing and learning an image matched to the same channel as the fog image with the fog image. Accordingly, it is possible to obtain a fog removal image with improved quality even for fog images in various actual situations.