Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)

A novel medical image fusion approach based on fractional wavelets transform

Authors
Na Zhang, Peiguang Wang, Haili Huang, Xiaoping Zong
Corresponding Author
Na Zhang
Available Online March 2017.
DOI
10.2991/mecae-17.2017.35How to use a DOI?
Keywords
Fractional Wavelets Transform, Local Energy Maximum, Multi-Modal Image Fusion.
Abstract

Multi-modal image fusion is a process of integrating complementary information from multiple images of different scene. A novel medical image fusion algorithm based on the fractional wavelets transform (FRWT) is proposed in this paper. The method is implemented to fractional wavelets transform to get highpass and lowpass wavelets coefficients. Then according to the different frequency fusion rules combine the coefficients to obtain the fused image. The performance of the proposed fusion method is assessed by experiment, and the results indicate the proposed method outperforms the traditional approaches.

Copyright
© 2017, 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 on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
10.2991/mecae-17.2017.35
ISSN
2352-5401
DOI
10.2991/mecae-17.2017.35How to use a DOI?
Copyright
© 2017, 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  - Na Zhang
AU  - Peiguang Wang
AU  - Haili Huang
AU  - Xiaoping Zong
PY  - 2017/03
DA  - 2017/03
TI  - A novel medical image fusion approach based on fractional wavelets transform
BT  - Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)
PB  - Atlantis Press
SP  - 184
EP  - 188
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-17.2017.35
DO  - 10.2991/mecae-17.2017.35
ID  - Zhang2017/03
ER  -