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

被引：299
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
相关论文
共 14 条
  • [1] An automatic image registration for applications in remote sensing
    Bentoutou, Y
    Taleb, N
    Kpalma, K
    Ronsin, J
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2005, 43 (09): : 2127 - 2137
  • [2] A SURVEY OF IMAGE REGISTRATION TECHNIQUES
    BROWN, LG
    [J]. COMPUTING SURVEYS, 1992, 24 (04) : 325 - 376
  • [3] The effects of image misregistration on the accuracy of remotely sensed change detection
    Dai, XL
    Khorram, S
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1998, 36 (05): : 1566 - 1577
  • [4] RANDOM SAMPLE CONSENSUS - A PARADIGM FOR MODEL-FITTING WITH APPLICATIONS TO IMAGE-ANALYSIS AND AUTOMATED CARTOGRAPHY
    FISCHLER, MA
    BOLLES, RC
    [J]. COMMUNICATIONS OF THE ACM, 1981, 24 (06) : 381 - 395
  • [5] Automatic Image Registration Through Image Segmentation and SIFT
    Goncalves, Hernani
    Corte-Real, Luis
    Goncalves, Jose A.
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2011, 49 (07): : 2589 - 2600
  • [6] Measures for an Objective Evaluation of the Geometric Correction Process Quality
    Goncalves, Hernani
    Goncalves, Jose A.
    Corte-Real, Luis
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2009, 6 (02) : 292 - 296
  • [7] A Novel Coarse-to-Fine Scheme for Automatic Image Registration Based on SIFT and Mutual Information
    Gong, Maoguo
    Zhao, Shengmeng
    Jiao, Licheng
    Tian, Dayong
    Wang, Shuang
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 52 (07): : 4328 - 4338
  • [8] RSCJ: Robust Sample Consensus Judging Algorithm for Remote Sensing Image Registration
    Li, Bin
    Ye, Hao
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2012, 9 (04) : 574 - 578
  • [9] A Simple and Robust Feature Point Matching Algorithm Based on Restricted Spatial Order Constraints for Aerial Image Registration
    Liu, Zhaoxia
    An, Jubai
    Jing, Yu
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2012, 50 (02): : 514 - 527
  • [10] Distinctive image features from scale-invariant keypoints
    Lowe, DG
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 2004, 60 (02) : 91 - 110
12