基于线状特征增强的TM遥感影像细小河流提取方法

测绘学报 ›› 2014, Vol. 43 ›› Issue (7): 705-710.

基于线状特征增强的TM遥感影像细小河流提取方法

姜浩¹,²,冯敏³,肖桐⁴,王昌佐⁴

1. 中国科学院大学
2. 中国科学院地理科学与资源研究所
3. University of Maryland, College Park
4. 环境保护部卫星环境应用中心

收稿日期:2013-12-09 修回日期:2014-02-10 出版日期:2014-07-20 发布日期:2014-07-29
通讯作者: 肖桐 E-mail:xt.earth@gmail.com
基金资助:
LUCC 对陆地生态系统的影响机制与多尺度LUCC 生态效应研究;资源与环境信息系统国家重点实验室自主部署创新研究计划资助项目;分布式计算环境下的地理空间模型松散耦合研究

A Narrow River Extraction Method Based on Linear Information Enhancement in TM image

Received:2013-12-09 Revised:2014-02-10 Online:2014-07-20 Published:2014-07-29

摘要/Abstract

摘要：

混合像元效应是导致难以从TM影像中提取细小河流的主要原因。提出一种综合多种数字图像处理技术的细小河流自动识别方法。首先，利用阈值分割区分水体指数影像中的细小河流与面状水体；第二，对水体指数进行线状信息增强，突出线状河流信息，并抑制其他地物信息；第三，利用双阈值线段追踪方法，提取影像中的细小河流；第四，通过三种方法分别去除阴影、道路和其他类型噪声。结果表明，本文方法能有效地提取细小河流，同时排除多种噪声的干扰，结果的检测率高于82%、虚警率低于7%、检测质量高于79%、完整度高于90%。

关键词: 细小河流, 遥感, 水体提取, 水体指数

Abstract:

Extraction of narrow rivers from TM images can be hardly achieved due to mixed-pixel effects. This paper presents an automatic approach for narrow river extraction by integrating multiple digital image processing techniques. Firstly, the threshold segmentation was applied on water-index images to separate from planar water bodies and narrow rivers. Secondly, a linear information enhancement algorithm is adopted to highlight river information and suppress other information. Thirdly, narrow rivers are extracted using dual-threshold line tracking method. Finally, three methods are selected to remove shadow, roads and other noises. Experimental results show the approach can effectively extract narrow rivers with the extraction rate higher than 82%, false alarm rate lower than 7%, extraction quality higher than 79%, and completeness higher than 90%, and avoid impact from multiple kinds of noise.

Key words: narrow river, remote sensing, water extraction, water index

中图分类号:

P237

姜浩冯敏肖桐王昌佐. 基于线状特征增强的TM遥感影像细小河流提取方法[J]. 测绘学报, 2014, 43(7): 705-710.

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