Multi-spectrum Image Fusion Algorithm Based on Weighted and Improved Wavelet Transform

被引：0
|
作者：
Wang, Zhiwen [1 ,2 ]
Li, Shaozi [1 ]
Cai, Qixian [2 ,3 ]
Su, Songzhi [1 ]
Lu, MeiZhen [4 ]
机构：
[1] Xiamen Univ, Dept Cognit Sci, Xiamen, Peoples R China
[2] Guangxi Univ Technol, Dept Comp Engn, Xiamen, Peoples R China
[3] Guangxi Univ Technol, Dept Comp Engn, Liuzhou, Peoples R China
[4] Guangxi Univ Technol, Lib, Liuzhou, Peoples R China
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 4 | 2009年
基金：
中国国家自然科学基金;
关键词：
multi-spectrum image; wavelet transform; image fusion; root mean square error; image information entropy; DECOMPOSITION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：63 / +
页数：2
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