DocumentCode
1928504
Title
Pixel-Level image Fusion Based on Fuzzy Theory
Author
Liu, Gang ; Lu, Xue-qin
Author_Institution
Shanghai Univ. of Electr. Power, Shanghai
Volume
3
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
1510
Lastpage
1514
Abstract
A new region based image fusion scheme is proposed. It is based on multiscale analysis. The low frequency band of the image multiscale representation is segmented into three kinds of regions by K-mean algorithm, which is used to determine the fusion rule and to achieve the multiscale representation of fusion result. The final image fusion result can be obtained by performing the inverse multiscale transform. The experiment demonstrates that the proposed image fusion method can illustrate better performance than exiting image fusion method.
Keywords
fuzzy set theory; image fusion; image representation; image segmentation; transforms; fuzzy set theory; image multiscale representation; image segmentation; inverse multiscale transform; pixel-level image fusion; Cybernetics; Discrete wavelet transforms; Equations; Filters; Frequency; Image fusion; Image segmentation; Machine learning; Pixel; Signal processing algorithms; Fuzzy theory; Image fusion; Information fusion; Signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370384
Filename
4370384
Link To Document