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一种基于ICA的多源图像融合算法
引用本文:曹杰,龚声蓉,刘纯平,姚望舒,刘全.一种基于ICA的多源图像融合算法[J].中国图象图形学报,2007,12(10):1857-1860.
作者姓名:曹杰  龚声蓉  刘纯平  姚望舒  刘全
作者单位:苏州大学计算机科学与技术学院 苏州215006
基金项目:国家自然科学基金;教育部科学技术研究重点项目;江苏省高校自然科学基金
摘    要:图像融合的要求是尽可能多地融合源图像中的有用信息,并尽量不要把无用信息融合进来。为了尽可能达到这一要求,在分析盲源分离理论的基础上,提出了一种基于独立分量分析(ICA)的图像融合算法。该算法首先对源图像进行预处理;然后对源图像进行ICA分解,并在ICA域对独立分量系数进行融合;最后根据融合系数重建融合图像。实验结果表明,该新提出的算法降低了产生冗余信息的可能性,对多源图像融合是可行有效的。

关 键 词:多源图像  图像融合  独立分量分析  矩阵稀疏性
文章编号:1006-8961(2007)10-1857-03
修稿时间:6/5/2007 12:00:00 AM

A Multi-source Image Fusion Algorithm Using ICA
CAO Jie,GONG Sheng-rong,LIU Chun-ping,YAO Wang-shu,LIU Quan,CAO Jie,GONG Sheng-rong,LIU Chun-ping,YAO Wang-shu,LIU Quan,CAO Jie,GONG Sheng-rong,LIU Chun-ping,YAO Wang-shu,LIU Quan,CAO Jie,GONG Sheng-rong,LIU Chun-ping,YAO Wang-shu,LIU Quan and CAO Jie,GONG Sheng-rong,LIU Chun-ping,YAO Wang-shu,LIU Quan.A Multi-source Image Fusion Algorithm Using ICA[J].Journal of Image and Graphics,2007,12(10):1857-1860.
Authors:CAO Jie  GONG Sheng-rong  LIU Chun-ping  YAO Wang-shu  LIU Quan  CAO Jie  GONG Sheng-rong  LIU Chun-ping  YAO Wang-shu  LIU Quan  CAO Jie  GONG Sheng-rong  LIU Chun-ping  YAO Wang-shu  LIU Quan  CAO Jie  GONG Sheng-rong  LIU Chun-ping  YAO Wang-shu  LIU Quan and CAO Jie  GONG Sheng-rong  LIU Chun-ping  YAO Wang-shu  LIU Quan
Affiliation:School of Computer Science and Technology, Soochow University, Suzhou 215006
Abstract:Image fusion technology should try to achieve two objectives: one is to combine useful information of source images as much as possible;the other is to abandon the useless information of source images.Based on the analysis of blind signal separation theory,an ICA-based image fusion algorithm is proposed in this paper.Firstly,some pre-processing methods and ICA analysis are applied to each source image;then the ICA coefficients computed in the first step are fused using the maximum rule.Finally the fused image is obtained by synthesizing the fused ICA coefficients.Experiments prove that the new algorithm is feasible and effective for multi-source images fusion.
Keywords:multi-source image  image fusion  independent component analysis(ICA)  matrix sparsity
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