| 基于规则信息的无人机图像建筑物提取 |
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| 引用本文： | 张湘宇,李向新,李万刚,孙路遥. 基于规则信息的无人机图像建筑物提取[J]. 软件, 2019, 0(5): 226-229 |
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| 作者姓名： | 张湘宇 李向新 李万刚 孙路遥 |
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| 作者单位： | 1.昆明理工大学国土资源工程学院;2.云南海钜地理信息技术有限公司 |
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| 摘 要： | 基于规则信息的无人机图像建筑物提取,首先要对待处理图像进行图像分割,经过大量的实验确定分割阈值为0.3,通过定义规则信息,解决了建筑物纹理特征与光谱特征与道路、裸地相似的问题,同时,将原始图像的提取结果和与进行主成分分析(PCA)处理后的图像的提取结果进行对比,证明了PCA后的图像提取精度高达85%。
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| 关 键 词： | 无人机图像 阈值分割 规则信息 建筑物提取 |
Building Extraction on Rule Information for UAV Image |
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| ZHANG Xiang-yu,LI Xiang-xin,LI Wan-gang,SUN Lu-yao. Building Extraction on Rule Information for UAV Image[J]. Software, 2019, 0(5): 226-229 |
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| Authors: | ZHANG Xiang-yu LI Xiang-xin LI Wan-gang SUN Lu-yao |
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| Affiliation: | (Kunming University of Science and Technology,Faculty of Land Resource Engineering,Kunming 650000;Yunnan Haiju Geographic Information Technology Co.,Ltd.,Kunming 650000) |
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| Abstract: | Based on the rule information,the UAV image building extraction firstly needs to process the image for image segmentation.After a large number of experiments,the segmentation threshold is 0.3.By defining the rule information,the problem that the texture features and spectral features of the building are similar to roads and bare land is solved.at the same time,comparing the extraction result of the original image with the extraction result of the image after performing principal component analysis (PCA),it is proved that the image accuracy after PCA is as high as 85%. |
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| Keywords: | UAV Image Image segmentation Rule information Building extraction |
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