[1]韩文军,孙小虎,吉根林,等.基于卷积神经网络的多光谱与全色遥感图像融合算法[J].南京师大学报(自然科学版),2021,44(03):123-130.[doi:10.3969/j.issn.1001-4616.2021.03.018]
　Han Wenjun,Sun Xiaohu,Ji Genlin,et al.Multispectral and Panchromatic Remote Sensing Image Fusion AlgorithmBased on Convolutional Neural Networks[J].Journal of Nanjing Normal University(Natural Science Edition),2021,44(03):123-130.[doi:10.3969/j.issn.1001-4616.2021.03.018]
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基于卷积神经网络的多光谱与全色遥感图像融合算法()
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《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

卷:
第44卷
期数:
2021年03期
页码:
123-130
栏目:
·计算机科学与技术·
出版日期:
2021-09-15

文章信息/Info

Title:
Multispectral and Panchromatic Remote Sensing Image Fusion AlgorithmBased on Convolutional Neural Networks
文章编号:
1001-4616(2021)03-0123-08
作者:
韩文军1; 孙小虎1; 吉根林2; 苏晓云3; 谢 非3; 吴 冰4; 陈 红5
(1.国家电网经济技术研究院有限公司,北京 102209)(2.南京师范大学计算机与电子信息学院,江苏 南京 210023)(3.南京师范大学南瑞电气与自动化学院,江苏 南京 210023)(4.浙江省电力有限公司经济技术研究院,浙江 杭州 310000)(5.江苏省电力有限公司经济技术研究院,江苏 南京 210008)
Author(s):
Han Wenjun1; Sun Xiaohu1; Ji Genlin2; Su Xiaoyun3; Xie Fei3; Wu Bing4; Chen Hong5
(1.State Grid Economic and Technology Research Institute Co. Ltd,Beijing 102209,China)(2.School of Computer and Electronic Information,Nanjing Normal University,Nanjing 210023,China)(3.School of Electrical and Automation Engineering,Nanjing Normal University,Nanjing 210023,China)(4.Economic and Technology Research Institute of Zhejiang Electric Power Co. Ltd,Hangzhou 310000,China)(5.Economic and Technology Research Institute of Jiangsu Electric Power Co. Ltd,Nanjing 210008,China)
关键词:
卷积神经网络; 多光谱图像; 全色图像; 融合算法
Keywords:
convolutional neural networks; multispectral image; panchromatic image; fusion algorithm
分类号:
TP751
DOI:
10.3969/j.issn.1001-4616.2021.03.018
文献标志码:
A
摘要:
地理信息数据具有不同分辨率、不同精度、不同覆盖范围等多尺度特征,在应用中往往需要同时具备高光谱分辨率和高空间分辨率两种信息的图像. 为提高多光谱图像和全色图像融合的准确性,提出了基于卷积神经网络的多光谱与全色遥感图像融合算法. 首先,对训练集内图像进行预处理,构建适用于本算法的图像数据集; 然后,拓展卷积神经网络卷积层,提高三通道关联性,提取更多图像信息; 最后,使用深度可分离卷积神经网络,提高融合图像的精度的同时,也加快了融合速度. 在Downsampled ImageNet数据集提供的原始图像上对算法融合准确度和速度进行了验证. 实验结果表明,相较于传统卷积神经网络算法,本文算法均方误差降低7%,融合时间减少了29%,具有较好的融合效果.
Abstract:
The geographic information data has multi-scale characteristics such as different resolution,different precision and different coverage. In application,it is often necessary to have both high spectral resolution and high spatial resolution images. In order to improve the accuracy of multispectral image and panchromatic image fusion,a fusion algorithm for multispectral and panchromatic remote sensing images based on convolutional neural networks is proposed. Firstly,the images in the training set is preprocessed to construct the image data set suitable for the algorithm. Secondly,the convolution layers of convolutional neural networks are expanded to improve the three channel correlation and extract more image information. Finally,the depth separable convolutional neural networks are used to improve the accuracy of the fusion image,which can also accelerate the fusion speed. The accuracy and speed of the algorithm are verified using the original images provided by downsampled ImageNet dataset. Experimental results show that the mean square error of the proposed algorithm is 7% lower and the fusion time is reduced by 29% compared with the traditional convolutional neural networks method,and obtain a good fusion effect.

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备注/Memo

备注/Memo:
收稿日期:2020-06-11.
基金项目:国家电网公司科技项目(5200-201956106A-0-0-00).
通讯作者:吉根林,博士,教授,博士生导师,研究方向:大数据分析与挖掘技术. E-mail:glji@njnu.edu.cn; 谢非,博士,副教授,研究方向:机器视觉与深度学习. E-mail:xiefei@njnu.edu.cn
更新日期/Last Update: 2021-09-15