Proceedings of the 2017 International Conference Advanced Engineering and Technology Research (AETR 2017)

The Improvement on the Maximum Mutual Information Image Registration

Authors
Xiaolei Zhao
Corresponding Author
Xiaolei Zhao
Available Online March 2018.
DOI
10.2991/aetr-17.2018.50How to use a DOI?
Keywords
Maximum mutual information; Wavelet decomposition; Image registration
Abstract

This paper studies the theory and algorithm based on the maximum mutual information image registration, And on that basis, the paper comes up with an idea of algorithm improvement to combine the wavelet decomposition with the theory and algorithm. This paper also proves from the theory and practice that the improved algorithm is superior to maximum mutual information image registration. In this paper, we can learn that the effect of the maximum mutual information image registration based on two layers of wavelet transformation is the best of all by comparing the different experimental dates.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference Advanced Engineering and Technology Research (AETR 2017)
Series
Advances in Engineering Research
Publication Date
March 2018
ISBN
10.2991/aetr-17.2018.50
ISSN
2352-5401
DOI
10.2991/aetr-17.2018.50How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xiaolei Zhao
PY  - 2018/03
DA  - 2018/03
TI  - The Improvement on the Maximum Mutual Information Image Registration
BT  - Proceedings of the 2017 International Conference Advanced Engineering and Technology Research (AETR 2017)
PB  - Atlantis Press
SP  - 258
EP  - 262
SN  - 2352-5401
UR  - https://doi.org/10.2991/aetr-17.2018.50
DO  - 10.2991/aetr-17.2018.50
ID  - Zhao2018/03
ER  -