Title :
A subspace identification extension to the phase correlation method [MRI application]
Author :
Hoge, William Scott
Author_Institution :
Harvard Med. Sch., Brigham & Women´´s Hosp., Boston, MA, USA
Abstract :
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 noninteger 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.
Keywords :
biomedical MRI; correlation methods; image registration; medical image processing; singular value decomposition; integer pixel displacements identification; limited computational complexity; magnetic resonance imaging; medical diagnostic imaging; noise robustness; noninteger pixel displacement identification; phase correlation method; subpixel phase correlation based techniques; Biomedical imaging; Correlation; Degradation; Fourier transforms; Image registration; Interpolation; Magnetic resonance imaging; Motion estimation; Phase change materials; Phase estimation; Algorithms; Artifacts; Citrus paradisi; Echo-Planar Imaging; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Motion; Signal Processing, Computer-Assisted; Statistics as Topic; Subtraction Technique;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2002.808359