Automatic Road Extraction Using Particle Filters from High Resolution Images

作     者：YE Fa-mao SU Lin TANG Jiang-long 

作者机构：Department of Computer Science and Engineering Nanchang University Nanchang Jiangxi 330029 China Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China East China Institute of Technology Fuzhou Jiangxi 344000 China 

出 版 物：《Journal of China University of Mining and Technology》 (中国矿业大学学报（英文版）)

年 卷 期：2006年第16卷第4期

页      面：490-493页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081002[工学-信号与信息处理] 

主　　题：road extraction particle filters high resolution images 

摘      要：Road extraction plays an important role in many applications such as car navigation, but the manual extraction of roads is a laborious, tedious task. To speed the extraction of roads, an approach based on particle filtering to extract automatically roads from high resolution imagery is proposed. Particle filtering provides a statistical framework for propagating sample-based approximations of posterior distributions and has almost no restriction on the ingredients of the model. We integrate the similarity of grey value and the edge point distribution of roads into particle filtering to deal with complex scenes. To handle road appearance changes the tracking algorithm is allowed to update the road model during temporally stable image observations. A fully automatic initialization strategy is used. Experimental results show that the proposed approach is a promising and fully automatic method for extracting roads from images, even in the presence of occlusions.