| 从卫星遥感全色图像中自动提取城市目标 |
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| 引用本文： | 文贡坚,李德仁,叶芬.从卫星遥感全色图像中自动提取城市目标[J].武汉大学学报(信息科学版),2003,28(2):212-218. |
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| 作者姓名： | 文贡坚 李德仁 叶芬 |
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| 作者单位： | 1. 武汉大学测绘遥感信息工程国家重点实验室,武汉市珞喻路129号,430079
2. 陕西省华阴市50信箱721分箱,710042 |
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| 基金项目： | 国家自然科学基金资助项目 ( 60 2 75 0 0 8，40 0 2 30 0 4)，中国博士后科学基金资助项目 |
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| 摘 要： | 提出了一种从卫星遥感全色图像中自动提取城市目标的方法。在总结城市目标的卫星遥感全色图像特性的基础上 ,设计了一种层次提取的方法。首先在低分辨率图像中提取城市目标的候选区域 ;接着在候选区域内利用城市目标一些更复杂的特性在高分辨率图像中证实城市目标。为了获得城市目标的边界 ,提出了一种基于边缘点密度的算法 ,并将算法应用去提取SPOT图像中的城市目标 ,取得了较好的试验结果
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| 关 键 词： | 卫星遥感图像分析 目标识别 目标提取 变化检测 |
| 文章编号： | 1671-8860(2003)02-0216-07 |
| 修稿时间： | 2002年12月15 |
Automatic Extraction of Urban Area from Satellite Panchromatic Remote Sensing Images |
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| WEN Gongjian , LI Deren YE Fen.Automatic Extraction of Urban Area from Satellite Panchromatic Remote Sensing Images[J].Geomatics and Information Science of Wuhan University,2003,28(2):212-218. |
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| Authors: | WEN Gongjian LI Deren YE Fen |
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| Institution: | WEN Gongjian 1,2 LI Deren 1 YE Fen 2 |
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| Abstract: | The process of extracting urban area from remote sensing images is an important step for monitoring and measuring urban change.In the existing literatures,many statistical approaches were developed to solve this difficult task,but there are few successful reports because the reflectance of an object usually does not characterize its nature.In this paper,we propose a structural method for automatic detection of urban area from satellite panchromatic remote sensing images.Urban area is a kind of complex combinatorial object and each urban area has its particular combinatorial mode,therefore it is difficult to describe an urban area model in detail.Through analyzing urban area structures and observing many real satellite panchromatic city images,we firstly summarize four common properties for most of an urban areas as follows:(1) an image of an urban area contains variation in pixel intensities; (2) an urban area has a large size; (3) for most of local images of an urban area,there are two main peaks in the orientation histogram of short lines which are extracted from a local image,and the orientation lap between the two peaks is about 90 degrees; (4) there are also two peaks in the orientation histogram of long lines,and the two peaks account for a majority of the histogram.Secondly,we follow these properties to devise a hierarchical method for extracting urban area from satellite panchromatic remote sensing images.In the first level,some candidate regions of urban area are segmented from low_resolution image based on the two former statistical properties.In the second level,the candidate regions are verified by computing the two latter complex geometric features of urban area from high_resolution image.We divide three steps to detect the candidate regions of an urban area.An input image is firstly sampled to create a low_resolution image,and then the sampled image is processed using histogram equalization and quantization and is segmented by computing texture energy features and exploiting split_and_merge algorithm.Finally,some large areas with high texture energy are selected as the candidate regions.After acquired the candidate regions,we use the two latter features of urban area to make further analysis.Because the two properties are based on the local range of an urban area image,therefore the candidate regions must be firstly divided into many sub_images,and then the procedure of urban area confirmation is implemented on each sub_image.The verification procedure is implemented into three steps.All straight lines are firstly extracted and binarized into short and long line sets using a defined threshold,and then two feature parameters are computed: one is the orientation lap between the two highest peaks of the orientation histogram of short line set; the other is equal to the sum of the two highest peaks of the orientation histogram of long line set.Finally,when the first parameters is close to 90 degrees and the second one is larger than 0.5,the sub_image is labeled as CITY,otherwise as NONCITY.In a candidate region,if the ratio of sub_images with CITY label is larger than 0.7,then it is an urban area.In order to smooth the boundary of an urban area,we propose an edge point density (EPD)_based method: first,EPD of all pixels are estimated to get an EPD image; in the second step,a two_threshold scheme is implemented to segment the EPD image; finally,two mathematical morphological operators are used to smooth the boundary of the urban area.We have embedded the proposed algorithm into a system developed by our laboratory for automatic complex object recognition and have tested many real SPOT remote sensing images.Experimental results have shown the feasibility of our algorithms. |
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| Keywords: | remote sensing image processing object recognition object extraction change detection |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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