Road network extraction in classified SAR images using genetic algorithm

被引：0
|
作者：
肖志强
鲍光淑
蒋晓确
机构：
[1] Central South University
[2] Central South University Changsha 410083
[3] China
[4] School of Info-Physics and Geomatics Engineering
来源：
Journal of Central South University of Technology(English Edition) | 2004年 / 02期
关键词：
genetic algorithm; road network extraction; SAR image; fuzzy C means;
D O I：
暂无
中图分类号：
TN957.52 [数据、图像处理及录取];
学科分类号：
080904 ; 0810 ; 081001 ; 081002 ; 081105 ; 0825 ;
摘要：
Due to the complicated background of objectives and speckle noise, it is almost impossible to extract roads directly from original synthetic aperture radar(SAR) images. A method is proposed for extraction of road network from high-resolution SAR image. Firstly, fuzzy C means is used to classify the filtered SAR image unsupervisedly, and the road pixels are isolated from the image to simplify the extraction of road network. Secondly, according to the features of roads and the membership of pixels to roads, a road model is constructed, which can reduce the extraction of road network to searching globally optimization continuous curves which pass some seed points. Finally, regarding the curves as individuals and coding a chromosome using integer code of variance relative to coordinates, the genetic operations are used to search global optimization roads. The experimental results show that the algorithm can effectively extract road network from high-resolution SAR images.
引用
收藏
页码：180 / 184
页数：5
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