一种高分辨率遥感影像快速自动道路提取方法
A Quickly Automatic Road Extraction Method for High-Resolution Remote Sensing Images

作者: 李 琳 :武汉大学遥感信息工程学院,湖北 武汉; 张 翔 :济南市勘察测绘研究院,山东 济南;

关键词: 高分辨率遥感影像自动道路提取分割线特征提取High-Resolution Remote Sensing Images Automatic Road Extraction Segmentation Line Extraction

摘要:
高分辨率遥感影像为用户提供丰富的地表细节信息,而如何利用这些细节信息获取地理目标,更新地理信息数据库,是遥感信息处理研究的热点也是难点之一。本文提出了一种高分辨率遥感影像快速自动提取道路的方法,这种方法以影像的分割和线特征提取为基础,综合利用道路的面状特征和线状特征,并利用面状特征道路对象应具有足够数量的线特征信息以及道路对象应具有较小形状指数的判断原则来提取和剔除道路对象。实验结果表明,这种方法能够从影像中较好地提取乡村的常规线性道路和城区具有较多面状区域的非常规道路。

Abstract: High-resolution images provide abundant surface details for users, so how to extract geographic objects with these details, to update geographic information database has become the issue of re-mote sensing information processing. This paper presents a fast automatic road extraction method of high-resolution remote sensing images. This approach, based on the fast image segmentation and line extraction, comprehensively utilizing the planar and linear feature information of the road, uses the judgment rule of planar road objects with sufficient line information and road objects with smaller shape index to extract and remove a road object. Experimental results show that this method can well extract conventional rural linear road and unconventional urban planar road.

文章引用: 李 琳 , 张 翔 (2015) 一种高分辨率遥感影像快速自动道路提取方法。 测绘科学技术, 3, 27-33. doi: 10.12677/GST.2015.32005

参考文献

[1] 李德仁 (2008) 摄影测量与遥感学的发展展望. 武汉大学学报•信息科学版, 12, 1211-1215.

[2] 史文中, 朱长青, 王昱 (2001) 从遥感影像提取道路特征的方法综述与展望. 测绘学报, 3, 257-261.

[3] 吕雪锋, 程承旗, 龚健雅, 关丽 (2011) 海量遥感数据存储管理技术综述. 中国科学: 技术科学, 12, 1561-1573.

[4] Tang, W. and Zhao, S.H. (2011) Road extraction in quaternion space from high spatial resolution remote sensed images basing on GVF Snake model. Journal of Remote Sensing, 15, 1040-1052.

[5] Lu, B.B., U, Y.X. and Wang, H. (2009) Automatic road extraction method based on level set an shape analysis. Intelligent Computation Technology and Automation, Changsha, 511-514.

[6] Lin, X.G., Hang, J.X., Heng, J., et al. (2009) Semiautomatic road tracking by template matching and distance transform. Urban Remote Sensing Event, Shanghai, 1-7.

[7] Zhang, L.J., Zhang, J., Hang, D.P., et al. (2010) Urban road extraction from high resolution remote sensing images based on semantic model. 2010 18th International Conference on Geoinformatics, Beijing, 18-20 June 2010, 1-5.

[8] 李晓峰, 张树清, 韩富伟, 秦喜文, 于欢 (2008) 基于多重信息融合的高分辨率遥感影像道路信息提取. 测绘学报, 2, 178-184.

[9] Mena, J.B. (2003) State of the art on automatic road extraction for GIS update: A novel classification. Pattern Recognition Letter, 24, 3037-3058.

[10] Das, S., Mirnalinee, T. and Varghese, K. (2011) Use of salient features for the design of a multistage framework to extract roads from high-resolution multispectral satellite images. IEEE Transactions on Geoscience and Remote Sensing, 49, 3906-3931.

[11] 李书晓, 常红星 (2007) 基于总变分和形态学的航空图像道路监测算法. 计算机学报, 2, 2173-2180.

[12] 巫兆聪, 胡忠文, 欧阳群东 (2011) 一种区域自适应的遥感影像分水岭分割算法. 武汉大学学报•信息科学版, 3, 293-296.

[13] Shao, Y.Z., Guo, B.X., Hu, X.Y. and Di, L.P. (2011) Application of a fast linear feature detector to road extraction from remotely sensed imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4, 626-631.

[14] Sun, C. and Vallotton, P. (2006) Fast linear feature detection using multiple directional non-maximum suppression. IEEE International Conference on Pattern Recognition, 2, 288-291.

[15] Hulshofrm (1995) Landscape indices describing a Dutch landscape. Landscape Ecology, 10, 101-111.

分享
Top