An image fusion algorithm based on RBF neural networks

被引：0

作者：

Gao, LQ ^{[1
]}

Wang, R ^{[1
]}

Yang, S ^{[1
]}

Chai, YH ^{[1
]}

机构：

[1] Northeastern Univ, Inst Informat Sci & Engn, Shenyang 110004, Peoples R China

来源：

PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9 | 2005年

关键词：

image fusion; RBF neural networks; wavelet transform; features extraction;

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：

An image fusion algorithm based on RBF neural networks for multi-focus image is presented in this paper. Four features are defined and proved to indicate the clarity of an image block, and these features are extracted and fed into the neural networks, which then learns to determine which source image is clearer at that particular physical location. The comparison of the algorithm proposed in this paper and the DWT-based one is done. Experimental results show that the performance of the method proposed in this paper is superior to that of DWT-based one.

引用

页码：5194 / 5199

页数：6