基于特征基元的高分辨率遥感影像城市空间信息提取

Research on Urban Spatial Information Extraction from High Resolution Remote Sensing Image Based on Feature Units

结合人类视觉机制和计算机尺度空间理论,设计了基于特征基元的高分辨率遥感影像多尺度信息提取技术模式,即先在大尺度上进行粗分割,再进行精细分割,获得特征基元并进行特征表达,通过样本分类和知识推理等实现信息的提取与目标识别。针对城市空间信息的特点,在特征基元提取的基础上,采用马尔可夫随机场纹理分类方法、直方图阈值分割方法、支撑向量机分类方法等完成对城市水体、建筑区、道路和绿化用地的分类提取,构建了一套从高分辨率遥感影像中提取城市空间信息的方法体系。

According to the characteristics of urban spatial information, this paper presents a multi-scale urban spatial information extraction mode of high-resolution remote sensing images based on feature units. Scale-transforming technique is emphasized in this mode. By rough-classification using region partition method based on GMRF-SVM, relatively great target areas and water body can be extracted firstly. And then, using block parcel unit extraction method based on histogram threshold segmentation and linear parcel unit extraction method based on edge detection, urban construction area, road area and vegetation area can be obtained respectively. Based on the extraction mode of feature units, a set of methods are built up to extract urban spatial information and recognize urban target areas from high-resolution remote sensing images. It is an effective tool to interpret and analyze urban spatial structure and configuration information.