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In this paper, an adaptive dual-regularization super-resolution reconstruction algorithm based on sub-pixel convolution (MPSR) is proposed. There are two novel features of the algorithm: First, the traditional regularization algorithm and sub-pixel convolution algorithm are combined to enrich the details; then, a regularization function with two adaptive parameters and two regularization terms is proposed to enhance the edge. MPSR firstly enhances the multi-scale detail of low-resolution images; then, regular processing and feature extraction are carried out; finally, sub-pixel convolution is used to fuse the extracted features to generate high-resolution images. The experimental results show that the subjective and objective evaluation indexes (PSNR/SSIM) of the algorithm have achieved satisfactory results.

Super-Resolution Reconstruction Algorithm for Infrared Image with Double Regular Items Based on Sub-Pixel Convolution