无线电工程2024，Vol.54Issue(1)：129-135,7.DOI:10.3969/j.issn.1003-3106.2024.01.017
多通道U型网络遥感影像变化检测
Change Detection of Remote Sensing Images with Multi-channel U-shaped Network
摘要
Abstract
Change detection of remote sensing images is an important research direction in the field of remote sensing,which plays an important role in many fields such as agriculture,disaster assessment,and urban construction.At present,most change detection tasks are completed using deep learning methods,but many existing deep learning networks have problems such as weak image feature extraction ability and inability to finely distinguish between change regions.A deep U-shaped network MCFFNet with multi-channel and multi-scale feature fusion is proposed.Firstly,the Unet network is extended to a three-channel structure,and the pre-classification feature information and fusion features of the corresponding scale feature images are obtained during the down-sampling process.Then,during the up-sampling process,the feature information of the corresponding scale is fused.Finally,the feature map is mapped into a single optimal change detection result map through convolutional activation and other operations.Experiments on the commonly used datasets CDD and WHU in the field of remote sensing image change detection have achieved higher change detection accuracy than the methods for comparison.关键词
遥感影像/变化检测/深度学习/特征融合/多通道/多尺度特征Key words
remote sensing image/change detection/deep learning/feature fusion/multi-channel/multi-scale feature分类
信息技术与安全科学引用本文复制引用
杜行奇..多通道U型网络遥感影像变化检测[J].无线电工程,2024,54(1):129-135,7.基金项目
国家级大学生创新创业训练计划(202011075013,202111075012)National Innovation and Entrepreneurship Training Program for College Students(202011075013,202111075012) （202011075013,202111075012）
