独立成分分析
图像融合
人工智能
模式识别(心理学)
融合
公制(单位)
计算机科学
领域(数学分析)
图像(数学)
图像分割
计算机视觉
分割
融合规则
数学
工程类
数学分析
哲学
语言学
运营管理
作者
Nedeljko Cvejic,David Bull,Nishan Canagarajah
标识
DOI:10.1109/jsen.2007.894926
摘要
In this paper, we present a novel multimodal image fusion algorithm in the independent component analysis (ICA) domain. Region-based fusion of ICA coefficients is implemented, where segmentation is performed in the spatial domain and ICA coefficients from separate regions are fused separately. The ICA coefficients from given regions are consequently weighted using the Piella fusion metric in order to maximize the quality of the fused image. The proposed method exhibits significantly higher performance than the basic ICA algorithm and also shows improvement over other state-of-the-art algorithms
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