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Numerical Methods for Image Registration$
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Jan Modersitzki

Print publication date: 2003

Print ISBN-13: 9780198528418

Published to Oxford Scholarship Online: September 2007

DOI: 10.1093/acprof:oso/9780198528418.001.0001

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SUMMARY OF PARAMETRIC IMAGE REGISTRATION

SUMMARY OF PARAMETRIC IMAGE REGISTRATION

Chapter:
(p.73) 7 SUMMARY OF PARAMETRIC IMAGE REGISTRATION
Source:
Numerical Methods for Image Registration
Author(s):

Jan Modersitzki

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198528418.003.0007

This chapter summarizes the techniques discussed so far in this book. The techniques are all based on the minimization of a certain distance measure, and the distance measure is based on image features or directly on image intensities. Image features can be user supplied (e.g., landmarks) or may be deduced automatically from the image intensities (e.g., principal axes). Typical examples of intensity-based distance measures are the sum of squared differences, correlation or mutual information. For all proposed techniques, the transformation is parametric, i.e., it can be expanded in terms of some parameters and basis functions. The desired transformation is a minimizer of the distance measure in the space spanned by the basis functions. The minimizer can be obtained from algebraic equations or by applying appropriate optimization tools.

Keywords:   distance measures, sum of squared differences, correlation, mutual information, optimization

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