[1]余 威,龙慧云.基于深度卷积网络的遥感影像建筑物分割方法[J].计算机技术与发展,2019,29(06):57-61.[doi:10. 3969 / j. issn. 1673-629X. 2019. 06. 012]
　YU Wei,LONG Hui-yun.A Building Segmentation Method Based on Deep Convolution Networks for Remote Sensing Imagery[J].,2019,29(06):57-61.[doi:10. 3969 / j. issn. 1673-629X. 2019. 06. 012]
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基于深度卷积网络的遥感影像建筑物分割方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年06期
页码:
57-61
栏目:
智能、算法、系统工程
出版日期:
2019-06-10

文章信息/Info

Title:
A Building Segmentation Method Based on Deep Convolution Networks for Remote Sensing Imagery
文章编号:
1673-629X(2019)06-0057-05
作者:
余 威; 龙慧云
贵州大学 计算机科学与技术学院,贵州贵阳 550025
Author(s):
YU Wei; LONG Hui-yun
School of Computer Science and Technology,Guizhou University,Guiyang 550025,China
关键词:
全卷机神经网络; 遥感影像; 建筑物分割; 模型融合
Keywords:
full convolution networks; remote sensing imagery; building segmentation; model fusion
分类号:
TP301
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 06. 012
摘要:
大规模可见光遥感图像的建筑物提取是遥感图像分析领域中的一项重要工作,但是,在真实环境下,城市建筑物的尺寸范围变化大、颜色纹理轮廓复杂,加上树木等造成的遮挡,以及光照等原因,影响建筑物分割的精度。 因此,文中设计并实现了两种端到端全卷积神经网络的分割方法,并在两个网络模型中加入剪裁层用以解决预测结果中产生的拼接痕迹问题,同时将 IOU 评价标准变形加入损失函数中,来提高模型分割精度。 两个模型以不同尺度的遥感影像作为网络的输入,将网络模型输出结果采用加权的方式进行融合,进一步提高遥感影像建筑物识别和分割精度。 在公开的 Inria 遥感影像数据集上的实验证明了该方法在遥感影像建筑物分割上的有效性。
Abstract:
Building extraction technique based on large-scale optical remote sensing images plays an important role in the field of remote sensing image analysis. But in the real environment,due to the big range of urban building爷s size,the complexity of building爷s colors, texture and contour,the occlusion of trees,as well as the illumination intensity,the precision of building segmentation is decreased. In order to improve the accuracy of building segmentation,two kinds of end-to-end full convolution networks (FCN) are proposed and realized,then crop layer is added to these two models to solve the visible boundary on predicted patches. Meanwhile IOU index are added into the loss function to improve the segmentation accuracy. These two networks use different scale images as input,and the two output images are fused in a weighted way. The experiment on Inria aerial imagery dataset shows that this method is effective in building segmentation of remote sensing imagery.

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更新日期/Last Update: 2019-06-10