基于对象直方图G统计量的遥感影像道路提取

提出了一种基于对象直方图G统计量的遥感影像道路提取方法。首先基于标记分水岭算法分割高分辨率遥感影像获取对象像斑，提取对象光谱特征并利用SVM从影像中分离出光谱相似的建成区（道路、建筑物等）；然后从建成区选择合适的对象作为训练样本，采用G统计量度量测试样本与训练样本的LBP纹理直方图距离，以表达对象纹理特征的异质性，并利用最小距离分类器完成建成区内道路与建筑物等的分离；最后结合几何形状特征和数学形态学处理对提取的道路进行优化，获得最终的道路提取结果。试验结果表明：该方法能较好地提取出道路信息。

Road Extraction of Remote Sensing Imagery Using G Statistics of Object Histogram

This paper proposes a new road extraction method of remote sensing imagery based on G statistics of object histogram .Firstly, the original imagery is segmented using marked-watershed algorithm to obtain imagery objects , and the imagery objects ' spectral features are extracted ,the built-up areas containing roads and buildings are separated based on SVM .Then the appropriate objects are chosen as training samples .G statistics is used to measure the histogram distance between test samples and training samples which describes the heterogeneity of two objects .Minimum distance classifier is employed to separate the road information and buildings in built-up areas.Finally,the final road information is extracted integrating the shape features and mathematics morphology .The result of experiment shows that the proposed method can fairly well extract the road information .