A Novel Point-Matching Algorithm Based on Fast Sample Consensus for Image Registration

被引：313
作者：
Wu, Yue [1 ]
Ma, Wenping [1 ]
Gong, Maoguo [1 ]
Su, Linzhi [1 ]
Jiao, Licheng [1 ]
机构：
[1] Xidian Univ, Int Res Ctr Intelligent Percept & Computat, Minist Educ, Key Lab Intelligent Percept & Image Understanding, Xian 710071, Peoples R China
来源：
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2015年 / 12卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Image registration; random sample consensus (RANSAC); remote sensing;
D O I：
10.1109/LGRS.2014.2325970
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：
Robustness and accuracy are the two main challenging problems in feature-based remote sensing image registration. In this letter, a novel point-matching algorithm is proposed. An improved random sample consensus (RANSAC) algorithm called fast sample consensus (FSC) is proposed. It divides the data set in RANSAC into two parts: the sample set and the consensus set. Sample set has high correct rate and consensus set has a large number of correct matches. An iterative method is put forward to increase the number of correct correspondences. A set of measures has been used to evaluate the registration result. The performance of the proposed method is validated on the evaluation of these measures and the mosaic images. FSC can get more correct matches than RANSAC in less number of iterations, iterative selection of correct matches algorithm and removal of the imprecise points algorithm effectively increase the accuracy of the result. Extensive experimental studies compared with three state-of-the-art methods prove that the proposed algorithm is robust and accurate.
引用
收藏
页码：43 / 47
页数：5
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