DocumentCode
2728256
Title
Multi-spectrum image fusion algorithm based on weighted and improved wavelet transform
Author
Wang, Zhiwen ; Li, Shaoz ; Cai, Qixian ; Su, Songzhi ; Liu, MeiZhen
Author_Institution
Cognitive Sci. Dept., Xiamen Univ., Xiamen, China
Volume
4
fYear
2009
fDate
20-22 Nov. 2009
Firstpage
63
Lastpage
66
Abstract
A multi-spectrum image fusion algorithm with weighted bi-orthogonal self-adaptive wavelet transform is put forward in this paper, which can make up for defects that there are faintness of image details in multi-spectrum image fusion of lower contrast image. The self-adaptive method of wavelet coefficient local model maximum which is weighted is used to fuse the high frequency components and the syncretism adaptive method is also chosen in the course of fusing low frequency coefficient. The capability of multi-spectrum image fusion is evaluated by calculating mean grads of image. The experimental results show that the fusion rule of our proposed method is more effective.
Keywords
image fusion; wavelet transforms; high frequency components; improved wavelet transform; low frequency coefficient; multispectrum image fusion algorithm; self-adaptive method; syncretism adaptive method; wavelet coefficient local model maximum; weighted bi-orthogonal self-adaptive wavelet transform; weighted wavelet transform; Cognitive science; Frequency; Fuses; Image fusion; Information filtering; Information filters; Libraries; Low pass filters; Phase distortion; Wavelet transforms; image fusion; image information entropy; multi-spectrum image; root mean square error; wavelet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-4754-1
Electronic_ISBN
978-1-4244-4738-1
Type
conf
DOI
10.1109/ICICISYS.2009.5357741
Filename
5357741
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