摘要
首先建立了粗配准模型。然后对影像进行边缘提取,采用Hough变换提取同名直线。利用同名直线交点构建虚拟点集并进行特征描述,通过几何约束和互信息方法提取初始同名点。最后采用RANSAC算法获取最终的匹配结果,并利用获取的同名点对构建三角网进行小面元纠正。实验结果表明:相对于传统的SIFT匹配算法,本文方法可提取更多的同名点,均方根误差(RMSE)可以控制在1个像素以内。
First,a coarse registration model was built.Second,after image edge extraction,Hough transform was employed to extract matched line.Virtual corner dataset was constructed on the basis of the matched lines,description of the dataset was performed,the initial homonymous points are extracted according to the constraint geometry and mutual information.Finally,RANSAC algorithm was used to obtain the final results of the matching,a great amount of high precision control point pairs are used to construct TIN for tiny facet primitive rectification.Experiment results demonstrate that the presented method can extract more matching points than that SIFT matching method can.The Root of Mean Square Error of the matching points obtained by this method is lower than 1 pixel.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2012年第6期1576-1580,共5页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(40771159)
吉林农业大学青年启动基金项目(201040)
关键词
遥感技术
配准
异源
高分辨率卫星影像
remote sensing technology
registration
multi-source
high resolution satellite images
