基于主曲线的遥感图像河岸线提取

Bankline extraction in remote sensing images using principal curves

针对遥感图像中河岸线提取存在不光滑、容易发生间断等问题,提出一种基于主曲线的河岸线提取方法。该方法在学习过程中结合多边形线(PL,polygonal line)算法和误差反向传播(BP,back propagation)算法,首先学习河流中心骨架主曲线表达,然后再根据提出的左右河岸点集分割方法获得图像中河流的左岸点集和右岸点集,分别学习左右河岸线主曲线的光滑参数表达,最终实现遥感图像中河流中心骨架和河岸线的矢量化描述。主曲线表达解决了河岸线不光滑问题,而左右河岸线分开学习有效解决了因河道窄而导致河岸线间断的问题。在实际遥感图像河流提取实验中,与现有几种河岸线提取方法的对比分析结果表明:基于主曲线的河岸线提取方法提取的河岸线具有更好的光滑性,可以较好地解决在河流较窄处发生间断的问题,所得的河岸线矢量化描述更便于存储和重建,并可作为河流区域的形状特征用于检测与识别。

In bankline extraction from remote sensing images, the results are usually rough and segmented. A new banldine extraction method based on the principal curves was proposed. In the learning process, the polygonal line （PL） algorithm and the error back propagation （BP） algorithm were combined. Firstly, the principal curve of the river centerline was learned. Then, a segmentation method was proposed to divide the riparian points into two sets which belong to the left and right bank respectively, and the smooth parameter expressions of the principal curves of the two banklines were given. Finally, the vector description of the river centerline and banklines in remote sensing images were realized. The principal curve descriptions made the extracted banklines smooth, and the separate learning of the two banklines ensured the integrity of the extracted banklines for even narrow fiver channels. Comparison with the existing methods through experiments on real remote sensing images shows that the proposed method can achieve better smoothness and can be used to solve the problem of discontinuity in narrower channel of a river. The resulting vector descriptions of banklines are more convenient for storage and reconstruction and can be used as shape features for the detection and identification of river area in images.