摘要
针对高分辨率航空遥感影像中线状目标的特点,提出一种结合区域和直线特征识别线状目标的方法。在基于标记点分水岭变换进行初始分割的基础上,利用关于目标的知识和区域邻接图(RAG)对感兴趣区域进行合并,得到最终检测结果。实验结果表明,本文方法可以有效地从遥感影像中提取线状目标。
This paper proposes an effective approach to extract linear obiect in high-resolution remote sensing image. The approach integrates the knowledge about the linear object to implement the watershed algorithm and guide the region merging and finally extract the linear object. First, theKalman filter algorithm is used to detect the straight line in the image, the center point of parallel line pairs and the minimum with dynamics larger than predefined threshold are utilized as marker point to modify the morphological gradient of the input image by geodesic reconstruction, the modified gradient image is then segmented by the watershed transform. The initial segmentation result is input to region merging process. This process applies the region adjacency graph （RAG） representation of the segmented regions and knowledge about the road to execute the region merging, which significantly reduce the merging time. The proposed scheme was tested on remote sensing images of 2 m resolution, and the results show that the extraction of road is quite promising.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2005年第8期689-693,共5页
Geomatics and Information Science of Wuhan University
基金
测绘遥感信息工程国家重点实验室开放研究基金资助项目(020101)。
关键词
图像分割
分水岭变换
卡尔曼滤波
道路提取
image segmentation
watershed transform
Kalman filter
road extraction
