Subspace identification extension to the phase correlation method

W. S. Hoge
IEEE Transactions on Medical Imaging
Volume 22, Number 2, Pages 277-280
Feb, 2003

Download full paper            DOI: 10.1109/TMI.2002.808359            PubMed: 12716003

Abstract

The phase correlation method 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 phase correlation method. In addition, this approach is shown to be complementary with other subpixel phase correlation based techniques.

 


Acquired MR Image Example: (a) Representative MR Image of a grapefruit acquired using a Fast Spin Echo Sequence, (b) Phase correlation matrix, Q, for grapefruit images 1 and 2, and (c) the rank one approximation constructed from the dominant singular vectors of Q. The D.C. component of the frequency domain coordinate system is at the center of the phase correlation matrices. Estimation of the shift between grapefruit images 1 and 2 can be determined by measuring the slope of the denoised gradient

Reference

Hoge WS. Subspace identification extension to the phase correlation method. IEEE Transactions on Medical Imaging 2003;22(2):277-280.

Bibtex entry

@Article{hogeTMI2003,
  author         = {Hoge, W. Scott},                                           
  title          = {Subspace identification extension to the phase correlation 
                   method},                                                    
  journal        = {IEEE Transactions on Medical Imaging},                     
  year           = 2003,                                                       
  volume         = 22,                                                         
  number         = 2,                                                          
  month          = {Feb},                                                      
  pages          = {277-280},                                                  
  pmid           = 12716003,                                                   
  doi            = {10.1109/TMI.2002.808359}
}

Grants

NIH T32-EB002177

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