Identification of translational displacements between N-dimensional data sets using the high-order SVD and phase correlation


This paper presents an extension of the phase correlation image alignment method to N-dimensional data sets. By the Fourier shift theorem, the motion model for translational shifts between N-dimensional images can be represented as a rank-one tensor. Through use of a high-order singular value decomposition, the phase correlation between two N-dimensional… (More)
DOI: 10.1109/TIP.2005.849327

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