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基于带滚动引导滤波器的字典学习的多聚焦图像融合

Multi-focus image fusion based on dictionary learning with rolling guidance filter.

作者信息

Yan Xiang, Qin Hanlin, Li Jia

出版信息

J Opt Soc Am A Opt Image Sci Vis. 2017 Mar 1;34(3):432-440. doi: 10.1364/JOSAA.34.000432.

Abstract

We present a new multi-focus image fusion method based on dictionary learning with a rolling guidance filter to fusion of multi-focus images with registration and mis-registration. First, we learn a dictionary via several classical multi-focus images blurred by a rolling guidance filter. Subsequently, we present a new model for focus regions identification via applying the learned dictionary to input images to obtain the corresponding focus feature maps. Then, we determine the initial decision map via comparing the difference of the focus feature maps. The latter is to optimize the initial decision map and perform it on input images to obtain fused images. Experimental results demonstrate that the suggested algorithm is competitive with the current state of the art and superior to some representative methods when input images are well registered and mis-registered.

摘要

我们提出了一种基于字典学习和滚动引导滤波器的新型多聚焦图像融合方法,用于融合配准和未配准的多聚焦图像。首先,我们通过滚动引导滤波器对几幅经典多聚焦图像进行模糊处理来学习一个字典。随后,我们通过将学习到的字典应用于输入图像以获得相应的聚焦特征图,提出了一种用于聚焦区域识别的新模型。然后,我们通过比较聚焦特征图的差异来确定初始决策图。后者是对初始决策图进行优化,并将其应用于输入图像以获得融合图像。实验结果表明,当输入图像配准良好和未配准时,所提出的算法与当前的先进技术具有竞争力,并且优于一些代表性方法。

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