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【答案】应助回帖
★ ★ ★ ★ ★
感谢参与，应助指数 +1
hopfliking: 金币+5, ★★★★★最佳答案 2014-09-21 19:37:40
sunshan4379: LS-EPI+1, 感谢应助！ 2014-09-22 17:56:50
A Novel Coarse-to-Fine Scheme for Automatic Image Registration Based on SIFT and Mutual Information
作者:Gong, MG (Gong, Maoguo)[ 1 ] ; Zhao, SM (Zhao, Shengmeng)[ 1 ] ; Jiao, LC (Jiao, Licheng)[ 1 ] ; Tian, DY (Tian, Dayong)[ 1 ] ; Wang, S (Wang, Shuang)[ 1 ]
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷: 52
期: 7
页: 4328-4338
DOI: 10.1109/TGRS.2013.2281391
出版年: JUL 2014
查看期刊信息
摘要
Automatic image registration is a vital yet challenging task, particularly for remote sensing images. A fully automatic registration approach which is accurate, robust, and fast is required. For this purpose, a novel coarse-to-fine scheme for automatic image registration is proposed in this paper. This scheme consists of a preregistration process (coarse registration) and a fine-tuning process (fine registration). To begin with, the preregistration process is implemented by the scale-invariant feature transform approach equipped with a reliable outlier removal procedure. The coarse results provide a near-optimal initial solution for the optimizer in the fine-tuning process. Next, the fine-tuning process is implemented by the maximization of mutual information using a modified Marquardt-Levenberg search strategy in a multiresolution framework. The proposed algorithm is tested on various remote sensing optical and synthetic aperture radar images taken at different situations (multispectral, multisensor, and multitemporal) with the affine transformation model. The experimental results demonstrate the accuracy, robustness, and efficiency of the proposed algorithm.
关键词
作者关键词:Image registration; mutual information (MI); outlier removal; scale-invariant feature transform (SIFT)
KeyWords Plus:SEGMENTATION; OPTIMIZATION
作者信息
通讯作者地址: Gong, MG (通讯作者)
[显示增强组织信息的名称] Xidian Univ, Key Lab Intelligent Percept & Image Understanding, Minist Educ China, Xian 710071, Peoples R China.
地址:
[显示增强组织信息的名称] [ 1 ] Xidian Univ, Key Lab Intelligent Percept & Image Understanding, Minist Educ China, Xian 710071, Peoples R China
电子邮件地址:gong@ieee.org
基金资助致谢
基金资助机构 授权号
National Natural Science Foundation of China
61273317
National Top Youth Talents Support Program of China
Fundamental Research Fund for the Central Universities
K50510020001
K5051202053
查看基金资助信息
出版商
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
类别 / 分类
研究方向:Geochemistry & Geophysics; Engineering; Remote Sensing; Imaging Science & Photographic Technology
Web of Science 类别:Geochemistry & Geophysics; Engineering, Electrical & Electronic; Remote Sensing; Imaging Science & Photographic Technology
文献信息
文献类型:Article
语种:English
入藏号: WOS:000332597100050
ISSN: 0196-2892
电子 ISSN: 1558-0644
期刊信息
目录： Current Contents Connect®
Impact Factor (影响因子): Journal Citation Reports®
其他信息
IDS 号: AC5YO
Web of Science 核心合集中的 "引用的参考文献": 39
Web of Science 核心合集中的 "被引频次": 0 |
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