东北大学学报(自然科学版) ›› 2012, Vol. 33 ›› Issue (11): 1547-1550.DOI: -

• 论著 • 上一篇    下一篇

基于多特征融合的遥感图像河流目标检测算法

于晓升;吴成东;陈东岳;田子恒;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-01-25
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(61005032);;

River detection in remote sensing image based on multi-feature fusion

Yu, Xiao-Sheng (1); Wu, Cheng-Dong (1); Chen, Dong-Yue (1); Tian, Zi-Heng (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-01-25
  • Contact: Yu, X.-S.
  • About author:-
  • Supported by:
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摘要: 针对近似河流无法准确检测出来的问题,提出了一种基于多特征融合的遥感图像河流目标检测算法.首先根据提取样本图像的局部熵、纹理和角点信息特征构建了有效区分河流区域和背景区域的特征向量,利用支持向量机进行训练获得决策函数,通过决策函数判断测试图像的河流区域,完成河流区域的粗检测;然后结合粗检测的结果,应用测地线活动轮廓模型提取完整准确的河流区域.实验结果证明该算法对河流目标定位准确,获得的河流检测结果具有良好的连通性,可以准确地检测复杂背景下的河流区域.

关键词: 多特征融合, 河流目标检测, 支持向量机, 测地线活动轮廓

Abstract: Due to the difficulties to exactly detect the similar rivers, a novel river detection algorithm was proposed based on multi-feature fusion of the remote sensing image. Firstly, the local entropy features, the texture features and corner information features of the simple images were extracted as the feature vectors of the support vector machine (SVM) in order to obtain the decision function. Then the decision function was employed to perform the coarse detection of rivers in tested images. Finally, in order to obtain the complete rivers, the geodesic active contour model was used, which was combined with the results of the coarse detection of rivers. Experimental results demonstrated the proposed algorithm has good performance in the location and connection of rivers, and the rivers can be detected accurately without the background interference.

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