基于卷积神经网络的单幅图像超分辨率重建算法综述

A review of super-resolution reconstruction of single image based on convolutional neural networks

近年来,单幅图像超分辨率重建技术成为机器视觉领域的研究热点.随着深度学习的发展,卷积神经网络在单幅图像超分辨率重建方面取得了前所未有的成功.文章对典型的图像超分辨率重建的卷积神经网络模型进行综合论述,比较分析了不同模型之间的异同点和优缺点,并对基于卷积神经网络的单幅图像超分辨率重建方法的未来研究方向进行展望.

In recent years,single image super-resolution reconstruction technology has become a research hotspot in the field of machine vision.With the development of deep learning,convolutional neural network has achieved unprecedented success in single image superresolution reconstruction.In this paper,the typical convolutional neural network model of image super-resolution reconstruction is discussed comprehensively,and the similarities and differences between different models are compared and analyzed.Finally,the future research direction of single image super-resolution reconstruction method based on convolutional neural network is prospected.