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遥感技术与应用  2008, Vol. 23 Issue (5): 545-550    DOI: 10.11873/j.issn.1004-0323.2008.5.545
图像处理     
基于图像匹配的星载遥感影像自动几何精校正算法
张多坤1,2,田兆申1,2,龙辉1,王宏琦1
(1.中国科学院电子学研究所,北京 100190;2.中国科学院研究生院,北京 100039)
A New Method for Automatic Geometric Rectification Based on Image Matching in Remote Sensing Image
ZHANG Duo-kun1,2,TIAN Zhao-shen1,2,LONG Hui1,WANG Hong-qi1
(1.Institute of Electronics of Chinese Academy of Sciences,Beijing 100190,China;
2.Graduate University of Chinese Academy of Sciences,Beijing 100039,China)
 全文: PDF(3269 KB)  
摘要:

提出了一种新的基于匹配技术的自动几何精校正算法,可以解决遥感影像人工几何纠正方法精度差、效率低等问题。该算法基于控制点图像片与待校正影像匹配实现控制点自动选取,然后进行异常匹配检测剔除匹配错误的控制点,保证控制点选择的精确性,并最后对遥感影像实施精校正。同时,根据以往研究成果,提出了一种更加快速、有效的多判据匹配算法。以遥感影像(光学/SAR)实例进行验证,结果证明了该方法的有效性和鲁棒性。

关键词: 图像匹配多判据匹配匹配错误检测几何精校正    
Abstract:

New method for automatic geometric rectification based on image matching in remote sensing image is proposed,which can solve the problem of lower-precision and time-consumption in traditional manual geometric rectification.First,the pictures contained ground control points (GCPs) are gained in the remote sensing image which has been processed with basic geometric correction method.Secondly,the accurate matching between remote sensing image and GCPs pictures are found.Then,the outliers of GCPs are detected.Finally,the remote sensing image is precisely corrected by the GCPs.Also in this paper,a new multicriterion image matching algorithm is proposed to detect precise matching.The experimental results demonstrate the robustness and effectiveness of the proposed automatic geometric rectification method.

Key words: Image matching    Multicriterion match    Match error detection    Automatism geometric rectification
收稿日期: 2008-03-31 出版日期: 2011-11-07
:  TP 75  
基金资助:

国家自然科学基金项目(40701110)。

作者简介: 张多坤(1982-),男,硕士研究生,主要从事信号与信息处理相关方面的研究。E-mail:dkzhang@ustc.edu。
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引用本文:

张多坤,田兆申,龙辉,王宏琦. 基于图像匹配的星载遥感影像自动几何精校正算法[J]. 遥感技术与应用, 2008, 23(5): 545-550.

ZHANG Duo-kun,TIAN Zhao-shen,LONG Hui,WANG Hong-qi. A New Method for Automatic Geometric Rectification Based on Image Matching in Remote Sensing Image. Remote Sensing Technology and Application, 2008, 23(5): 545-550.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2008.5.545        http://www.rsta.ac.cn/CN/Y2008/V23/I5/545

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