摘要
提出一种基于局部灰度一致性的图像分割方法并结合形状特征进行道路提取的方法。该方法首先对图像进行分割,对分割结果使用形状特征进行道路段的选择,可以获取直线和曲线道路段,克服了许多方法只能提取直线道路段的缺点,然后在确定的道路段上选择种子点进行区域增长,从而实现自动选取种子点并提取道路网的过程,最后结合边缘信息和形态学方法规整化道路网。提出的方法能适用于高分辨率遥感图像中直线和曲线道路段的提取。经过实验分析和比较证明:该方法对于路面灰度均匀性较好和路面灰度均匀性较差的图片,都达到了较好的效果。
Road extraction from high-resolution remote sensing image is an important and difficult task.Since remote sensing images include complicated information,the methods that extract roads by spectral,texture and linear features have certain limitations.Also,many methods need human-intervention to get the road seeds（semi-automatic extraction）,which have the great human-dependence and low efficiency.The road-extraction method,which uses the image segmentation based on principle of local gray consistency and integration shape features, is proposed in this paper. Firstly, the image is segmented, and then the linear and curve roads are obtained by using several object shape features, so the method that just only extract linear roads are rectified. Secondly, the step of road extraction is carried out based on the region growth, the road seeds are automatic selected and the road net- work is extracted. Finally, the extracted roods ore regulated by combining the edge information. In experiments, the images that including the better gray uniform of road and the worse illuminated of road surface were chosen, and the results prove that the method of this study is promising.
出处
《测绘学报》
EI
CSCD
北大核心
2009年第5期457-465,共9页
Acta Geodaetica et Cartographica Sinica
关键词
遥感影像分割
道路提取
形状特征
道路种子点
区域增长
remote sensing image segmentation
road extraction
shape features
road seeds
region growth
