均值漂移与卡尔曼滤波相结合的遥感影像道路中心线追踪算法  

Tracking Road Centerlines from Remotely Sensed Imagery Using Mean Shift and Kalman Filtering

作　　者：曹帆之 朱述龙 朱宝山 李润生 孟伟灿[1] 

机构地区：[1]信息工程大学地理空间信息学院,河南郑州450000

出　　处：《测绘学报》2016年第2期205-212,223,共9页Acta Geodaetica et Cartographica Sinica

基　　金：国家自然科学基金(41401462)~~

摘　　要：基于模板匹配的道路追踪方法是道路提取中较实用的一类方法,但传统模板匹配方法主要以相关系数作为相似性测度,对车辆、树荫等遮挡敏感,不适用于高分辨率遥感影像道路提取。针对这一问题,本文采用一种稳健的相似性测度,设计了一种基于均值漂移的道路中心点匹配算法,克服了传统模板匹配对遮挡敏感的缺点;然后运用卡尔曼滤波,实现高分辨率遥感影像道路中心线追踪。试验表明,该方法能够准确提取高分辨率遥感影像道路中心线,对车辆、树荫等遮挡具有稳健性。Road tracking based on template matching is one class of practical methods of road extraction.However,the conventional methods of template matching mainly utilize correlation coefficient as the similarity measure.As a result,these algorithms are sensitive to occlusions caused by vehicles and trees and are unsuitable for road extraction from high-resolution remotely sensed imagery.To address this problem,this paper designs a road center matching algorithm based on mean shift utilizing a robust similarity measure,which overcomes the sensitivity of correlation coefficient matching to occlusions;then Kalman filter is utilized to track road centerlines from high-resolution remotely sensed imagery.Experimental results demonstrate that the proposed method can extract road centerlines from high-resolution remotely sensed imagery accurately and is robust to occlusions caused by vehicles and trees.

关 键 词：高分辨率遥感影像 道路提取 道路中心线追踪 模板匹配 均值漂移 卡尔曼滤波 

分 类 号：P237[天文地球—摄影测量与遥感]