Adaptive Image Fusion Using Ica Bases
Adaptive Image Fusion Using Ica Bases
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DOI：
10.1109/icassp.2006.1660471
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发表时间：
2006-05
期刊：
影响因子：
--
通讯作者：
N. Mitianoudis;T. Stathaki
中科院分区：
文献类型：
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作者：
N. Mitianoudis;T. Stathaki
图像融合可以看作是将来自不同模态传感器的基本信息合并到合成图像中的过程。利用独立分量分析（ICA）训练的基底进行图像融合是近年来研究的热点。通用的融合规则可用于ICA融合框架，并取得了良好的效果。本文提出了一种基于ICA融合框架的自适应融合方案，使融合图像在变换域中的稀疏性最大化
Image fusion can be viewed as a process that incorporates essential information from different modality sensors into a composite image. The use of bases trained using independent component analysis (ICA) for image fusion has been highlighted recently. Common fusion rules can be used in the ICA fusion framework with promising results. In this paper, the authors propose an adaptive fusion scheme, based on the ICA fusion framework, that maximises the sparsity of the fusion image in the transform domain