广西师范大学学报（自然科学版）2018，Vol.36Issue(2)：33-41,9.DOI:10.16088/j.issn.1001-6600.2018.02.005
基于卷积神经网络超分辨率重建的遥感图像融合
Remote Sensing Image Fusion Based on Convolutional Neural Network Super-resolution Reconstruction
摘要
Abstract
A remote sensing image fusion method based on super-resolution reconstruction with convolutional neural network (CNN)is proposed to make full use of spatial information of multispectral image and obtain better fusion quality.Firstly,the mulispectral image is transformed with IHS transform,the gotten I component is reconstructed by Super-Resolution Convolutional Neural Network (SRCNN),which enhances the spatial information while expanding its size.Then the panchromatic image and the reconstructed I component of mulispectral image are fused with the fusion method based on wavelet transform,the fusion rule is the absolute value and the changed high frequency components of the fusion image are all derived from the panchromatic image in the traditional algorithms.Finally,the fused multispectral image is obtained via inverse IHS transform.The experiment results show that the algorithm outperforms other algorithms,and reduces the loss of spatial information and spectral information in the process of image fusion effectively.关键词
遥感/图像融合/超分辨率重建/卷积神经网络Key words
remote sensing/image fusion/super-resolution reconstruction/convolutional neural network分类
信息技术与安全科学引用本文复制引用
薛洋,曾庆科,夏海英,王文涛..基于卷积神经网络超分辨率重建的遥感图像融合[J].广西师范大学学报（自然科学版）,2018,36(2):33-41,9.基金项目
国家自然科学基金(61762014),广西研究生教育创新计划项目(XYCSZ2017054) （61762014）
