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遥感技术与应用  2012, Vol. 27 Issue (5): 692-698    DOI: 10.11873/j.issn.1004-0323.2012.5.692
图像与数据处理     
综合灰度与纹理特征的高分辨率星载SAR图像建筑区提取方法研究
徐 佳1,2,陈媛媛1,黄其欢1,3,何秀凤1
(1.河海大学地球科学与工程学院,江苏 南京 210098;2.中国矿业大学国土资源与灾害监测国家测绘局重点实验室,江苏 徐州 221116;3.河海大学文天学院,安徽 马鞍山 243031)
Built-up Areas Extraction in High Resolution Spaceborne SAR Image based on the Integration of Grey and Texture Features
Xu Jia1,2,Chen Yuanyuan1,Huang Qihuan1,3,He Xiufeng1
(1.School of Earth Sciences and Engineering,Hohai University,Nanjing 210098,China;2.Key Lab for Land Environment and Disaster Monitoring of SBSM,China University of Mining and Technology,Xuzhou 221116,China;3.Wentian College,Hohai University,Maanshan 243031,China)
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摘要:

高分辨率SAR图像的纹理特性对于图像的解译及地物分类等具有重要的意义。根据高分辨率星载SAR图像上建筑区的纹理有别于其他地物的特点,提出了一种综合利用灰度和纹理特征的高分辨率星载SAR图像建筑区提取方法。首先对SAR图像进行斑点噪声的抑制,然后利用灰度共生矩阵计算出星载SAR图像上建筑区与非建筑区的8种纹理特征统计量,根据巴氏距离进行特征选择,并通过主成分分析去除纹理特征之间的相关性,得到了最佳纹理特征分量,将所选的特征影像与原始图像进行波段组合,利用K均值聚类算法对组合后的图像进行非监督分类;最后通过对分类图像进行后处理并提取外部轮廓,提取了建筑区。以COSMO-SkyMed SAR影像为数据源进行了实验。结果表明该方法能够有效提取高分辨率星载SAR图像中的建筑区,提取效果明显优于未利用纹理特征的方法。

关键词: 星载合成孔径雷达建筑区提取纹理特征灰度共生矩阵    
Abstract:

The texture features of high-resolution spaceborne SAR image is of great significance to image interpretation and classification.As the texture features of high-resolution spaceborne SAR image is different from other objects which appear in SAR images,a novel method for built-up areas extraction using both grey-scale and texture features is proposed in this paper.Firstly,reducing the speckles of the SAR image,then eight texture feature statistics of the built-up areas and non-building areas are calculated by using GLCM.Secondly,the best window size of GLCM is discussed and the texture features are selected according to the Bhattacharyya distance.Then,two principal components of the richest information are selected as the best texture components based on the principal component analysis method,and combine with the original image.Finally,the new image is classified with K-means classification method and the built-up areas are extracted after some post classification process.The proposed method has been tested by COSMO-SkyMed SAR image.The results show that this method can effectively extract built-up areas in the high-resolution spaceborne SAR image and is better than the method without using the texture features.

Key words: Spaceborne synthetic aperture radar    Built-up areas extraction    Texture feature    Gray Level Co-occurrence Matrix (GLCM)
收稿日期: 2011-11-21 出版日期: 2012-10-17
:  TP 75  
基金资助:

国土资源与灾害监测国家测绘局重点实验室开放基金资助项目(LEDM2011B02),中央高校基本科研业务经费资助项目(2009B12014),江苏省博士后基金资助项目(0901031C),高等学校优秀青年人才基金项目(2011SQRL170)。

 

作者简介: 徐 佳(1983-),女,湖北荆州人,博士,讲师,主要从事遥感信息提取与应用方面的研究。Email:cyy880421@126.com。
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引用本文:

徐 佳,陈媛媛,黄其欢,何秀凤. 综合灰度与纹理特征的高分辨率星载SAR图像建筑区提取方法研究[J]. 遥感技术与应用, 2012, 27(5): 692-698.

Xu Jia,Chen Yuanyuan,Huang Qihuan,He Xiufeng. Built-up Areas Extraction in High Resolution Spaceborne SAR Image based on the Integration of Grey and Texture Features. Remote Sensing Technology and Application, 2012, 27(5): 692-698.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2012.5.692        http://www.rsta.ac.cn/CN/Y2012/V27/I5/692

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