Image registration using wavelet-based motion model

Yu Te Wu, Takeo Kanade, Ching Chung Li, Jeffrey Cohn

Research output: Contribution to journalArticlepeer-review

70 Scopus citations

Abstract

An image registration algorithm is developed to estimate dense motion vectors between two images using the coarse-to-fine wavelet-based motion model. This motion model is described by a linear combination of hierarchical basis functions proposed by Cai and Wang. The coarserscale basis function has larger support while the finer-scale basis function has smaller support. With these variable supports in full resolution, the basis functions serve as large-to-small windows so that the global and local information can be incorporated concurrently for image matching, especially for recovering motion vectors containing large displacements. To evaluate the accuracy of the wavelet-based method, two sets of test images were experimented using both the wavelet-based method and a leading pyramid spline-based method by Szeliski et al. One set of test images, taken from Barron et al., contains small displacements. The other set exhibits low texture or spatial aliasing after image blurting and contains large displacements. The experimental results showed that our wavelet-based method produced better motion estimates with error distributions having a smaller mean and smaller standard deviation.

Original languageEnglish
Pages (from-to)129-152
Number of pages24
JournalInternational Journal of Computer Vision
Volume38
Issue number2
DOIs
StatePublished - Jul 2000

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