Improved Super-resolution Reconstruction of Infrared Images Based on Deep Back-projection Networks
轩 刘, 晨晖 马, 仁浦 林, 力 张, 豪 张 · Infrared Technoiogy · 2020
Deep back-projection networks have excellent performance in the super-resolution reconstruction of visual images.This paper explores the application of deep back-projection networks to the super-resolution reconstruction of infrared images.In view of the characteristics of low infrared image contrast and low image quality,the following improvements were made in the framework of the deep back-projection network:adding a concatenation layer before the upsampling module,cascading the previous downsampling output and the original low-resolution preprocessed image as the input of the upsampling module.This was designed to improve the network’s ability to obtain high-frequency information of the image and enhance the detail of the generated image.The experimental results proved that the proposed algorithm could create infrared super-resolution reconstructed images with richer details and improved visual effects.