Abstract: At present, due to environmental interference in the process of digital image acquisition and transmission, low-pixel images will appear, resulting in poor image reconstruction effect. For this reason, a digital image super-resolution reconstruction algorithm based on multi-scale residual is proposed. Use bilateral filtering algorithm to complete the dehazing processing of digital images. The brightness feature information and color information of digital images are classfied, and the distance threshold denoising method is used to denoise. To set convolution kernels of multiple sizes. In the process of image feature extraction, digital image features are obtained, and back-projection operations are performed on them. Based on the residual learning idea, the features extracted by the up-sampling and down-sampling processes are connected to realize digital image super-resolution reconstruction. The experimental results show that the proposed algorithm has high structural similarity, high PSNR (Peak Signal-to-Noise Ratio) and good reconstruction effect for image reconstruction. 

Key words: multid-scale residues, bilateral filtering algorithms, distance threshold removal method, residual learning, image super-resolution reconstruction