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利用边缘密度特征提取高分辨率遥感影像中的居民区
引用本文:陈洪,陶超,邹峥嵘,邵磊. 利用边缘密度特征提取高分辨率遥感影像中的居民区[J]. 应用科学学报, 2014, 32(5): 537-542. DOI: 10.3969/j.issn.0255-8297.2014.05.016
作者姓名:陈洪  陶超  邹峥嵘  邵磊
作者单位:中南大学地球科学与信息物理学院,长沙410083
基金项目:国家“973”重点基础研究发展计划基金
摘    要:居民区相对于其他区域具有更明显更丰富的边缘特征. 根据这一特点,提出一种利用边缘密度特征差异
进行高分辨率遥感影像居民区自动提取的方法. 该方法首先利用Mean Shift 算法平滑原始影像,然后检测平滑影
像上的边缘并拟合成直线段,最后利用影像中的边缘密度分布构建空间投票矩阵,并结合Ostu 阈值分割方法提取
居民区. 实验表明:该方法可用于提取场景比较复杂的影像中的居民区,且具有较高的准确率和鲁棒性.

关 键 词:高分辨率遥感影像  居民区提取  Mean Shift 算法  边缘密度特征  空间投票  
收稿时间:2012-10-24
修稿时间:2013-02-22

Extraction of Built-Up Areas Extraction from High-Resolution Remote-Sensing Images Using Edge Density Features
CHEN Hong,TAO Chao,ZOU Zheng-rong,SHAO Lei. Extraction of Built-Up Areas Extraction from High-Resolution Remote-Sensing Images Using Edge Density Features[J]. Journal of Applied Sciences, 2014, 32(5): 537-542. DOI: 10.3969/j.issn.0255-8297.2014.05.016
Authors:CHEN Hong  TAO Chao  ZOU Zheng-rong  SHAO Lei
Affiliation:School of Geosciences and Info-physics, Central South University, Changsha 410083, China
Abstract:Built-up area contains obvious edge features. We propose a method to extract edge-based built-up
area from high resolution remote sensing images. The algorithm includes three steps: smoothing the original
image with a mean shift algorithm, extracting edges with the Canny operator and fitting them as several
straight lines, and forming a spatial voting matrix based on the edge distribution and extracting the built-up
area using the Ostu’s method. Experimental results show that the proposed approach can detect built-up areas
in images with complicated background. It is highly robust and accurate.
Keywords:high resolution remote sensing image  built-up area extraction  Mean Shift algorithm  edge density features  spatial voting
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