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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Published in | Computer Analysis of Images and Patterns Vol. 8047; pp. 564 - 571 |
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Main Authors | , , , |
Format | Book Chapter |
Language | English |
Published |
Germany
Springer Berlin / Heidelberg
2013
Springer Berlin Heidelberg |
Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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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. |
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ISBN: | 3642402607 9783642402609 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-642-40261-6_68 |