矢量图约束的遥感影像分割算法

Remote sensing image segmentation under vector map constraints

为了解决矢量图约束下的遥感影像分割问题,提出了一种基于标记分水岭的带约束的影像分割方法。该方法首先将约束矢量图映射为影像中的边缘,在带边缘的影像上提取标记区域;然后采用面积约束法剔除伪标记区域,并利用优先级队列对未标记点进行泛洪;最后依据相似性测度对影像中的边缘点进行标号,将标号图矢量化获取影像分割结果。采用Quick Bird影像进行了实验,结果表明:该方法能够实现矢量图约束下的影像分割,当影像数据量较大时,比e Cognition软件中多尺度分割方法的运行效率高。

In order to solve the problem of remote sensing image segmentation under vector map constraints, this paper proposes a marker -based watershed method for remote sensing image segmentation under vector map constraints. Firstly, the constrained vector map is mapped to the edge of the image. The markers are extracted in the image with edge. Secondly, the pseudo marked areas are eliminated by area constraint. The flood for unmarked pixels is implemented by a priority queue arrow. Lastly, the edge pixels in the image are labeled by a similarity measurement. The label image is used for vectorization to get the segmentation result. The experimental result on the QuickBird image shows that the proposed method can realize image segmentation under vector map constraints. Compared with muhiresolution segmentation method in eCognition software, the proposed method is more efficient when the remote sensing image is large.