结合统计和形状特征的高分辨率SAR影像道路网提取

Temporal Semantic Characteristics of Spatial Entities’ Attributes and an Algebraic Framework

  • 摘要: 结合高分辨率SAR影像统计特性和道路形状特征,提出一种新的道路网提取方法。首先引入窗口均值改进二值分割,以降低SAR影像固有斑点的噪声影响,针对高分辨率影像中道路呈现为面特征并存在宽度变化的情况,引入VC系数自适应调整窗口大小,从而有效提取可能的道路区域;然后利用道路的形状特征约束,去除非道路区域;最后通过空洞填充、腐蚀和膨胀等数学形态学运算,以及骨骼化和去除多余分支等处理,提取道路网络。实验证实了本文方法的有效性。

     

    Abstract: atial,temporal and attributive characters are the three basic characters of spatial entities.Temporal attributes change over time.Research and Modeling on temporal attributes’ temporal semantics are important in spatiotemporal data modeling field.In this paper,in the form of algebraic relation,an attributive function is proposed,based on which,the temporal semantics of independent variable,domain of definition,function’s relation and function’s value are analyzed,and the algebraic descriptions,definitions and classifications of them are presented.At last,a classification with 20 types of temporal attributes are motivated which is able to offer advanced support for data modeling on temporal attributes,research on operation and query language,and presentation techniques in temporal geographical information system(TGIS).

     

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