首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >A novel multi-focus image fusion method using PCNN in nonsubsampled contourlet transform domain
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A novel multi-focus image fusion method using PCNN in nonsubsampled contourlet transform domain

机译:非下采样contourlet变换域中使用PCNN的多焦点图像融合新方法

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摘要

A novel multi-focus image fusion method using modified pulse coupled neural network (PCNN) in non-subsampled contourlet transform (NSCT) domain is presented in this study. Different scales and directions are obtained by image decomposition using the NSCT at first. Then to retain more edges and textures, the edge feature is used to motive the improved PCNN model. The coefficients in the NSCT domain with large firing times are selected as coefficients of the fused image. To testify the performance of our proposed algorithm, simulation experiments are conducted on it. The experimental results showed that the proposed algorithm produces better results compared to other state-of-the-art algorithms neither visual effects nor objective indicators. (C) 2015 Elsevier GmbH. All rights reserved.
机译:提出了一种在非下采样轮廓波变换(NSCT)域中使用改进的脉冲耦合神经网络(PCNN)的新型多焦点图像融合方法。首先,使用NSCT通过图像分解获得不同的比例和方向。然后,为了保留更多的边缘和纹理,使用边缘特征来驱动改进的PCNN模型。选择具有大触发时间的NSCT域中的系数作为融合图像的系数。为了验证我们提出的算法的性能,对其进行了仿真实验。实验结果表明,与其他既没有视觉效果也没有客观指标的最新算法相比,该算法产生了更好的结果。 (C)2015 Elsevier GmbH。版权所有。

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