Research on image super-resolution reconstruction algorithms based on deep learning

Image super-resolution reconstruction (ISRR) can reconstruct a high-resolution image from low-resolution images, and ISRR algorithms based deep learning (DL) networks appear to be one of the most promising directions. Motivated by recent studies, this paper summarizes the ISRR algorithms based on DL, with a focus on convolutional neural network algorithms, deep residual network algorithms and other typical algorithms. Based on the above analysis, a very deep super-resolution (VDSR) algorithm is proposed, and experimental verification on the DIV2K dataset is conducted as well. Furthermore, the important highlights and prospects of DL-based ISRR algorithm innovation are introduced.