一种基于双重网络模型的单幅图像超分辨率方法

A Single Image Super-Resolution Method Based on the Dual Network Model

本文对深度学习领域中的高效亚像素卷积神经网络(efficient sub-pixel convo-lutional neural network,ESPCN)算法进行了改进,通过加入残差网络知识,调整原有的ESPCN构造结构,提出了一种双重网络模型下单幅图像超分辨率重建方法。通过实验证明:该算法能够有效地提高单幅图像超分辨率重建的精度,丰富重建后的细节信息。

This article mainly improves the efficient sub-pixel convolutional neural network(ESPCN)algorithm in the field of deep learning.By adding residual network knowledge and adjusting original ESPCN structure,a dual network model is proposed for single frame image super-resolution reconstruction method.Experimental results show that this algo-rithm can effectively improve the accuracy of single-image super-resolution reconstruction and enrich the detailed information after reconstruction.