Multi-Focus Image Fusion via Boundary Finding and Multi-Scale Morphological Focus-Measure

Yu Zhang, X. Bai, Tao Wang
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引用次数: 2

Abstract

Multi-focus image fusion is to extract the focused regions from the multiple images of the same scene and combine them together to produce one fully focused image. The key is to find the focused regions from the source images. In this paper, we transform the problem of finding the focused regions to find the boundaries between the focused and defocused regions in the source images, and propose a novel image fusion method via boundary finding and a multi-scale morphological focus-measure. Firstly, a morphological focus-measure, consisted of multi- scale morphological gradients, is proposed to measure the focus of the images. Secondly, a novel boundary finding method is presented, which utilizes the relations of the focus information of the source images. Thirdly, the found boundaries naturally segment the source images into regions with the same focus condition and the focused regions can be simply selected by comparing the focus-measures of the corresponding regions. Fourthly, the detected focused regions are reconstructed to obtain the decision map for the multi-focus image fusion. Finally, the fused image is produced according to the decision map and the given fusion rule. Experimental results demonstrate the proposed algorithm outperforms other spatial domain fusion algorithms.
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基于边界发现和多尺度形态焦点测量的多焦点图像融合
多焦点图像融合是从同一场景的多幅图像中提取焦点区域,并将它们组合在一起,得到一幅完全聚焦的图像。关键是从源图像中找出聚焦区域。本文将寻找焦点区域的问题转化为寻找源图像中焦点和散焦区域之间的边界问题,提出了一种基于边界发现和多尺度形态学焦点测量的图像融合方法。首先,提出了一种由多尺度形态梯度组成的形态学焦点测量方法来测量图像的焦点。其次,利用源图像焦点信息之间的关系,提出了一种新的边界查找方法;第三,找到的边界自然地将源图像分割成具有相同聚焦条件的区域,通过比较相应区域的聚焦度量,可以简单地选择聚焦区域。第四,对检测到的聚焦区域进行重构,得到多聚焦图像融合的决策图;最后,根据决策图和给定的融合规则生成融合图像。实验结果表明,该算法优于其他空间域融合算法。
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