基于线状特征增强的TM遥感影像细小河流提取方法

A Narrow River Extraction Method Based on Linear Feature Enhancement in TM Image

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。本文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,利用阈值分割来区分水体指数影像中的细小河流与面状水体;然后,对水体指数进行线状特征增强,突出线状河流信息,并抑制其他地物信息;再利用双阈值线段追踪方法,提取影像中的细小河流;最后通过3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,结果的制图精度高于82%,用户精度高于93%,Kappa系数高于0.993,完整度高于90%。

Extraction of narrow rivers from TM images is challenging 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 feature 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 producer's accuracy higher than 82%,user's accuracy higher than 93%,Kappa coefficient higher than 0.993,and completeness higher than 90%,and avoid impact from multiple kinds of noise.