基于分水岭算法的高分遥感图像道路提取优化方法

Optimized method for road extraction from high resolution remote sensing image based on watershed algorithm

针对高分辨率遥感图像城市道路提取中存在的问题,在面向对象方法和数学形态学等理论基础上,提出了一种基于改进的分水岭分割算法的道路提取方法。在图像预处理基础上,首先使用改进的分水岭算法分割影像,提取基本的道路信息;然后利用面向对象方法提取道路基元,完善道路信息;最后将道路信息二值化,并采用数学形态学等方法进行优化,去除和修补不完善的道路。结果表明,该方法能有效地提取出城市地区的道路信息,对较复杂的道路环境也有较好的效果。

To tackle the problems existent in road information extraction from high resolution remote sensing,the authors put forward an improved approach to road extraction based on watershed segmentation according to the basic theories of object-oriented method and mathematical morphology.Firstly,the image is processed by improved watershed segmentation to extract basic road information after preprocessing.Then object-oriented method is used to extract road per-parcel so as to optimize the road extraction results.Finally,after binary image processing,the incomplete results can be removed and corrected by using mathematical morphological transformation.Experimentation shows that the proposed method can extract urban road information efficiently and process the roads from the complex urban context fairly satisfactorily.