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遥感技术与应用  2014, Vol. 29 Issue (5): 873-877    DOI: 10.11873/j.issn.1004-0323.2014.5.0873
图像与数据处理     
一种基于SIFT特征的快速逐层遥感图像配准方法
侯鹏洋1,季艳1,2,高峰1,胡蕾1,3
(1.北京航空航天大学计算机学院数字媒体北京市重点实验室,北京100191;
2.北京遥感信息研究所,北京100011;
3.江西师范大学计算机信息工程学院,江西 南昌330022)
Fast Hierarchical Registration Method for Remote Sensing Image based on SIFT
Hou Pengyang1,Ji Yan1,2 ,Gao Feng1,Hu Lei1,3
(1.Beijing Key Laboratory of Digital Media,School of Computer Science and Engineering,
Beihang University,Beijing 100191,China;
2.Beijing Institute of Remote Sensing Information,Beijing 100011,China;
3.School of Computer Information Engineering,Jiangxi Normal University,Nanchang 330022,China)
 全文: PDF(3432 KB)  
摘要:

当前SIFT特征分层配准方法中存在特征点匹配复杂度高以及不同时相地物变化导致特征点误匹配等问题,提出一种基于SIFT特征的“低分辨率配准\,高分辨率验证”快速逐层遥感图像配准方法。该方法针对同源同分辨率不同时相的遥感图像,通过在金字塔的低分辨率图层匹配特征点对并建立仿射变换模型,在金字塔的高分辨率图层评估并修正模型。实验表明:提出的方法在保证配准精度的前提下,有效提高了配准算法的效率。

关键词: 遥感图像图像配准SIFT变化检测    
Abstract:

For the current automatic image registration based on SIFT,feature point matching algorithm is time\|consuming,in addition,the changes of multi\|temporal images affect the accuracy of registration,this paper proposes a SIFT\|based feature of the “low\|resolution matching,high resolution authentication” hierarchical image registration algorithm to improve the above issues.In the proposed algorithm,affine transformation model is established in low\|resolution pyramid images and sequentially evaluated and revised by match points in high resolution pyramid images.Experimental results show that the improved SIFT algorithm can reduce the time complexity with rather considerable accuracy.

Key words: Remote sensing image    Image registration    SIFT    Change detection
收稿日期: 2013-07-09 出版日期: 2014-11-10
:  TP 75  
基金资助:

国家杰出青年科学基金项目(61125206)和国家自然科学基金项目(61262036)资助。

作者简介: 侯鹏洋(1988-),男,山东威海人,硕士研究生,主要从事遥感图像处理方面的研究。Email:houpengyang0901@126.com。
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引用本文:

侯鹏洋,季艳,高峰,胡蕾. 一种基于SIFT特征的快速逐层遥感图像配准方法[J]. 遥感技术与应用, 2014, 29(5): 873-877.

Hou Pengyang,Ji Yan,Gao Feng,Hu Lei. Fast Hierarchical Registration Method for Remote Sensing Image based on SIFT. Remote Sensing Technology and Application, 2014, 29(5): 873-877.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2014.5.0873        http://www.rsta.ac.cn/CN/Y2014/V29/I5/873

[1]Zitova B,Flusser J.Image Registration Methods:A Survey[J].Image and Vision Computing,2003,21(11):977-1000.

[2]Viola P A,Wells W M.Alignment by Maximization of Mutual Information[J].International Journal of Computer Vision,1997,24(2):16-23.

[3]Li Rui,Wang Juanle,Guo Fusheng,et al.Automatic Registration Method for Different Temporal Remote Sensing Images on Improved Fourier-Mellin Algorithm[J].Computer Engineering and Applications,2010,46(16):178-181.[李锐,王卷乐,郭复胜,等.Fourier-Mellin 变换不同时相遥感影像自动配准研究[J].计算机工程与应用,2010,46(16):178-181.]

[4]Pei Y J,Wu H,Yu J,et al.Effective Image Registration based on Improved Harris Corner Detection[C]//International Conference on InformationNetworking and Automation (ICINA),2010:93-96.

[5]Misra I,Moorthi S M,Har D,et al.An Automatic Satellite Image Registration Technique based on Harris Corner Detection and Random Sample Consensus(RANSAC) Outlier Rejection Model[C]//1st International Conference on Recent Advances in Information Technology (RAIT).Dhanbad.2012:68-73.

[6]Jiang J,Cao S X,Zhang G G.Shape Registration for Remote-Sensing Images with Background Variation[J].International Journal of Remote Sensing,2013,34(15):5265-5281.

[7]Zhang S M,Jiang J,Cao S X.Relative Shape Context based on Multi-scale Edge Features For Disaster Remote Sensing Image Registration[C]//3rdInternational Conference on Intelligent Control and Information Processing (ICICIP),Dalian,2012:605-609.

[8]Hasan M,Jia X P,Robles-Kelly,et al.Multi-spectral Remote Sensing Image Registration via Spatial Relationship Analysis on Sift Keypoints[C]//Geoscience and Remote Sensing Symposium (IGARSS),Honolulu HI,2010:1011-1014.

[9]Ouyang Nengjun,Li Weitong,Wei Wei,et al.Registration Technique for High-resolution Remote Sensing Images based on SIFT and Contourlet Transform[J].Remote Sensing Technology and Application,2013,28(1):58-64.[欧阳能钧,李伟彤,韦蔚.基于SIFT与Contourlee变换分辨遥感图像配准[J].遥感技术与应用,2013,28(1):58-64.]

[10]El Rube I A,Sharks M A,Salem A R.Image Registration based on Multi-scale SIFT for Remote Sensing Images[C]//3rd International Conference on SignalProcessing and Communication Systems(ICSPCS),Omaha,NE,2009:1-5.

[11]Zhu Y X,Cheng S,Stankovic V,et al.Image Registration Using BP-SIFT[J].Journal of Visual Communication and Image Representation,2013,24(4):448-457.

[12]Song Z,Li S,George T.Remote Sensing Image Registration Approach based on a Retrofitted SIFT Algorithm and Lissajous-curve Trajectories[J].OpticsExpress,2010,18(2):513-522.

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