Research on Image Super Resolution Reconstruction Model Based on Deep Learning

Abstract

Artificial neural network has made the rapid development of artificial intelligence with its super-learning ability, making artificial neural network become a research hotspot again. At present, deep learning has been widely used in various fields such as computer vision, speech processing, and natural language processing, and has even played a leading role in some fields. The single image super-resolution reconstruction technique aims to reconstruct a low-resolution image through a series of algorithms to reconstruct a corresponding high-resolution image. This paper first briefly introduces the relevant theories of artificial neural networks, then studies the fast super-resolution reconstruction model, and improves the model layer and filter size to establish a new improved model.