基于假设检验的数字影像线状特征亚像素自动提取  

Auto-extracting Sub-pixel Line Feature of Digital Images Based on Hypothesis Testing

作　　者：李畅[1] 李芳芳[2] 

机构地区：[1]华中师范大学城市与环境科学学院,湖北武汉430079 [2]国防科学技术大学信息系统工程重点实验室,湖南长沙410073

出　　处：《测绘学报》2013年第1期67-72,共6页Acta Geodaetica et Cartographica Sinica

基　　金：国家自然科学基金(41101407;41001260);湖北省自然科学基金(2010CDZ005);华中师范大学中央高校基本科研项目(CCNU10A01001)

摘　　要：线状特征是数字图像处理与模式识别中一种重要的中层描述符号,具有丰富的语义信息。针对目前提取算法的不足,提出一种稳健的高精度直线提取算法。在对分裂线段感知编组时提出一个基于假设检验的方法,从几何拓扑关系和物理光谱信息两个方面以及全局与局部两个尺度进行模糊融合和检验。并利用最小二乘模板匹配将提取直线的精度提高到亚像素。本算法可在一定程度上克服线段提取中的两类错误和定位精度低的问题,通过对航空和地面影像的试验,验证了该方法的有效性。Line feature,which has abundant semantic information,is a very important intermediate level symbol in digital image processing and pattern recognition.In order to resolve many issues in current line extraction algorithms,a robust and sub-pixel approach for extracting straight lines is presented.When fractured short line segments need to be combined into groups,which is called as perceptual organization,an algorithm based on hypothesis testing and fuzzy fusion is put forward.This algorithm combines fractured line segments into a whole one according to geometric topology,physics spectral information,global and local scale information.Then,the least square template matching algorithm（LSTM） is implemented to get the higher precise line segments.The experimental results show that the proposed algorithm is more efficient,which can get richer and sub-pixel straight lines from aerial and ground images.

关 键 词：线状特征亚像素提取 感知编组 假设检验 模糊融合 最小二乘模板匹配 霍夫变换 

分 类 号：P234[天文地球—摄影测量与遥感]