Global Image Registration Using Random Projection and Local Linear Method

The purpose of this paper is twofold. First, we introduce fast global image registration using random projection. By generating many transformed images as entries in a dictionary from a reference image, nearest-neighbour-search (NNS)-based image registration computes the transformation that establis...

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Bibliographic Details
Published inComputer Analysis of Images and Patterns Vol. 8047; pp. 564 - 571
Main Authors Itoh, Hayato, Sakai, Tomoya, Kawamoto, Kazuhiko, Imiya, Atsushi
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2013
Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
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Summary:The purpose of this paper is twofold. First, we introduce fast global image registration using random projection. By generating many transformed images as entries in a dictionary from a reference image, nearest-neighbour-search (NNS)-based image registration computes the transformation that establishes the best match among the generated transformations. For the reduction in the computational cost for NNS without a significant loss of accuracy, we use random projection. Furthermore, for the reduction in the computational complexity of random projection, we use the spectrum-spreading technique and circular convolution. Second, for the reduction in the space complexity of the dictionary, we introduce an interpolation technique into the dictionary using the linear subspace method and a local linear property of the pattern space.
ISBN:3642402607
9783642402609
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-40261-6_68