A subspace identification extension to the phase correlation method

被引:164
|
作者
Hoge, WS
机构
[1] Harvard Univ, Sch Med, Boston, MA 02115 USA
[2] Brigham & Womens Hosp, Boston, MA 02115 USA
关键词
phase correlation method; subpixel image registration; SVD;
D O I
10.1109/TMI.2002.808359
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The phase correlation method (PCM) is known to provide straightforward estimation of rigid translational motion between two images. It is often claimed that the original method is best suited to identify integer pixel displacements, which has prompted the development of numerous subpixel displacement identification methods. However, the fact that the phase correlation matrix is rank one for a noise-free rigid translation model is often overlooked. This property leads to the low complexity subspace identification technique presented here. The combination of non-integer pixel displacement identification without interpolation, robustness to noise, and limited computational complexity make this approach a very attractive extension of the PCM. In addition, this approach is shown to be complementary with other subpixel phase correlation based techniques.
引用
收藏
页码:277 / 280
页数:4
相关论文
共 50 条
  • [1] Subspace extension to phase correlation approach for fast image registration
    Ren, Jinchang
    Vlachos, Theodore
    Jiang, Jianmin
    2007 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-7, 2007, : 481 - +
  • [2] Polynomial extension of linear subspace algorithms for stochastic identification
    Di Loreto, C
    Germani, A
    Manes, C
    2004 43RD IEEE CONFERENCE ON DECISION AND CONTROL (CDC), VOLS 1-5, 2004, : 2213 - 2218
  • [3] An estimation method for InSAR interferometric phase using correlation weight joint subspace projection
    Hai Li
    Renbiao Wu
    EURASIP Journal on Advances in Signal Processing, 2013
  • [4] An estimation method for InSAR interferometric phase using correlation weight joint subspace projection
    Li, Hai
    Wu, Renbiao
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2013,
  • [5] Extending the subspace method for blind identification
    Imperial Coll, London, United Kingdom
    Int Conf Signal Process Proc, (347-350):
  • [6] Extending the subspace method for blind identification
    Hoteit, L
    ICSP '98: 1998 FOURTH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, PROCEEDINGS, VOLS I AND II, 1998, : 347 - 350
  • [7] A bilinear extension of subspace identification for systems subject to white inputs
    Favoreel, W
    DeMoor, B
    VanOverschee, P
    PROCEEDINGS OF THE 1997 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 1997, : 607 - 611
  • [8] Hankel Matrix Correlation Function-Based Subspace Identification Method for UAV Servo System
    She, Minghong
    Zhao, Pengju
    INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING, 2018, 2018
  • [9] A subspace projection method for blind identification using shifted correlation matrices (SPAWC-2004)
    Fang, J
    Leyman, AR
    Chew, YH
    2004 IEEE 5TH WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, 2004, : 527 - 531
  • [10] Compound Mutual Subspace Method for 3D Object Recognition: A Theoretical Extension of Mutual Subspace Method
    Akihiro, Naoki
    Fukui, Kazuhiro
    COMPUTER VISION - ACCV 2010 WORKSHOPS, PT II, 2011, 6469 : 374 - 383