• DocumentCode
    981428
  • Title

    Subpixel estimation of shifts directly in the Fourier domain

  • Author

    Balci, Murat ; Foroosh, Hassan

  • Author_Institution
    Sch. of Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
  • Volume
    15
  • Issue
    7
  • fYear
    2006
  • fDate
    7/1/2006 12:00:00 AM
  • Firstpage
    1965
  • Lastpage
    1972
  • Abstract
    In this paper, we establish the exact relationship between the continuous and the discrete phase difference of two shifted images, and show that their discrete phase difference is a two-dimensional sawtooth signal. Subpixel registration can, thus, be performed directly in the Fourier domain by counting the number of cycles of the phase difference matrix along each frequency axis. The subpixel portion is given by the noninteger fraction of the last cycle along each axis. The problem is formulated as an overdetermined homogeneous quadratic cost function under rank constraint for the phase difference, and the shape constraint for the filter that computes the group delay. The optimal tradeoff for imposing the constraints is determined using the method of generalized cross validation. Also, in order to robustify the solution, we assume a mixture model of inlying and outlying estimated shifts and truncate our quadratic cost function using expectation maximization.
  • Keywords
    Fourier analysis; expectation-maximisation algorithm; image registration; image resolution; matrix algebra; Fourier domain; continuous phase difference; discrete phase difference; expectation maximization; frequency axis; generalized cross validation; group delay; mixture model; noninteger fraction; overdetermined homogeneous quadratic cost function; phase difference matrix; rank constraint; shape constraint; shifted images; subpixel estimation; subpixel registration; two-dimensional sawtooth signal; Cost function; Delay; Filters; Frequency; Image analysis; Interpolation; Magnetic resonance imaging; Phase estimation; Robustness; Shape; Phase correlation; registration; subpixel alignment; Algorithms; Artificial Intelligence; Computer Graphics; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Statistical; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Signal Processing, Computer-Assisted; Subtraction Technique;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2006.873457
  • Filename
    1643703