摘要
提出了一种从IKONOS多光谱影像提取城市主要道路的方法。首先对影像进行3个层次的纹理分析。第一层为检测集像元与训练集像元在波段空间中的闵氏距离;第二层为检测集像元及其3×3窗口内像元分布与训练集像元在波段空间中的巴氏距离;第三层为检测集像元及其3×3窗口内像元分布与训练集像元在彩色纹理特征空间中的巴氏距离。对上述获取的结果分别进行了阈值分割、细化,并结合道路的几何特征,采用模糊数学的方法对各个图层进行了融合。接着提出了一种基于道路知识的道路段连接算法。最后用多项式拟合方法对连接结果进行了优化,获得了较好的提取结果。
A method for urban major road extraction from IKONOS imagery is proposed.The texture features of the imagery were first analyzed in three different levels.The first level calculated the Mahalanobis distance between test pixels and training pixels.The second level calculated the Bhattacharyya distance between the distributions of the pixels in the training area and the pixels within a 3×3 window in the test area.The third level employed cooccurrence matrices over the texture cube built around one pixel,and then calculated Bhattacharyya distance.The processed results were thresholded and thinned,respectively.With the assistance of the geometrical characteristic of roads,the three resultant images corresponding to three levels were merged by fuzzy mathematics.A knowledge-based algorithm was used to link the segmented roads.The result was finally optimized by polynomial fitting.The experiment shows that the proposed method can effectively extract the major urban roads from the high-resolution imagery such as IKONOS.
出处
《遥感技术与应用》
CSCD
北大核心
2010年第2期189-194,共6页
Remote Sensing Technology and Application
基金
国家自然科学基金资助项目(40371107)
福建省重大专项前期研究项目(2005YZ1011)
