Title :
Pixel-Level image Fusion Based on Fuzzy Theory
Author :
Liu, Gang ; Lu, Xue-qin
Author_Institution :
Shanghai Univ. of Electr. Power, Shanghai
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;
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
DOI :
10.1109/ICMLC.2007.4370384