Multi-focus image fusion with online sparse dictionary learning

Jun Wang, Lu Liu, Xuan Zhu, Na Ai, Kun Yan
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引用次数: 3

Abstract

This paper presents an effective multi-focus image fusion method based on the online sparse dictionary learning with double sparsity model. First, we learn the dictionaries through the source images using the online sparse dictionary learning algorithm, which enables a multi-scale analysis and train an adaptive dictionary. Then, the sparse representation coefficients of the source images may be acquired by the learned dictionary. Finally, the fused image is formed by choosing the max fusion rule and the learned dictionary. Experimental results show that the proposed method is superior to the conventional fusion methods in terms of the visual and indicator evaluation.
基于在线稀疏字典学习的多焦点图像融合
提出了一种基于双稀疏度模型的在线稀疏字典学习的多焦点图像融合方法。首先,我们使用在线稀疏字典学习算法通过源图像学习字典,实现多尺度分析并训练自适应字典。然后,通过学习字典获取源图像的稀疏表示系数。最后,通过选择最大融合规则和学习到的字典形成融合图像。实验结果表明,该方法在视觉效果和指标评价方面都优于传统的融合方法。
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