基于格式塔形状分析的高分辨率遥感影像道路提取

Road Extraction from High Resolution Remote Sensing Image based on Shape Analysis with Gestalt Theory

针对高分辨率遥感影像道路网的复杂性,模拟人眼视觉的心理感受,提出一种基于格式塔的道路分离模型,从形状学的角度对高分辨率遥感影像中的道路进行提取。首先基于光谱和纹理信息,使用分割技术提取出疑似道路的目标;然后按照疑似目标的实心度将其分类,对每一类分别进行道路目标提取。最后对3类识别出的道路信息进行验证与合并,得到连续光滑的道路提取结果。在真实的高分影像上进行实验.发现结果与人眼视觉感受一致,且总体分类精度较高,说明算法有效可行,有良好的使用价值。

Simulating the psychological experience of human vision,a road extraction model based on the format tower is proposed to extract the road in the high resolution remote sensing image from the perspective of morphology.Firstly,based on the spectral and texture information,the suspected road targets are extracted by using segmentation technology.Then these targets are classified according to their reliability and extract the road targets for each category.Finally,three types of identified road information are verified and merged,and the continuous smooth road extraction results are obtained.Experiments on real high resolution images show that the results are consistent with the visual perception of the human eye,and the overall classification accuracy is higher,indicating that the algorithm is effective and feasible and has good use value.