Multilevel SIFT Matching for Large-Size VHR Image Registration

被引：67

作者：

Huo, Chunlei ^{[1
]}

Pan, Chunhong ^{[1
]}

Huo, Leigang ^{[2
]}

Zhou, Zhixin ^{[3
]}

机构：

[1] Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China

[2] Xidian Univ, Dept Computat Math, Xian 710071, Peoples R China

[3] Beijing Inst Remote Sensing, Beijing 100854, Peoples R China

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2012年 / 9卷 / 02期

关键词：

Coarse-to-fine strategy; geometric constraint; large-size image registration; parallel-based architecture;

D O I：

10.1109/LGRS.2011.2163491

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

A fast approach is proposed in this letter for large-size very high resolution image registration, which is accomplished based on coarse-to-fine strategy and blockwise scale-invariant feature transform (SIFT) matching. Coarse registration is implemented at low resolution level, which provides a geometric constraint. The constraint makes the blockwise SIFT matching possible and is helpful for getting more matched keypoints at the latter refined procedure. Refined registration is achieved by blockwise SIFT matching and global optimization on the whole matched keypoints based on iterative reweighted least squares. To improve the efficiency, blockwise SIFT matching is implemented in a parallel manner. Experiments demonstrate the effectiveness of the proposed approach.

引用

页码：171 / 175

页数：5

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