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

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 multispectrum 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 multispectrum 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.

关键词： Keywords- multi-spectrum image wavelet transform image fusion root mean square error image information entropy

作者: Zhiwen WANG Songzhi SU Shaozi LI Qixian CAI MeiZhen LIU

作者单位: Cognitive Science Department of Xiamen University Department of Computer & Engineering,GXUT Xiamen,C Cognitive Science Department of Xiamen University Xiamen,China Department of Computer & Engineering,GXUT Liuzhou,china Library,Guangxi University of Technology Liuzhou,china

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 2592-2595

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）