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Medical image fusion method based on lifting wavelet transform and dual-channel PCNN

机译:基于提升小波变换和双通道PCNN的医学图像融合方法

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In order to further improve the quality of medical image fusion, the study proposes a medical image fusion method based on lifting wavelet transform(LWT) and dual-channel pulse coupled neural network( PCNN). A fusion rule based on region spatial frequency is adopted in low frequency sub-band coefficient. Dual-channel PCNN has a simpler network architecture and better adaptability. It takes less time-consuming and cuts down computational complexity in the process of large amoumt of medical images. Dual-channel PCNN fusion rule is adopted in high frequency sub-band coefficients. The experiment results show that the proposed method can greatly improve the quality of fusion image compared with traditional fusion methods and has less time-consuming with less computational complexity.
机译:为了进一步提高医学图像融合的质量,研究提出了一种基于提升小波变换(LWT)和双通道脉冲耦合神经网络(PCNN)的医学图像融合方法。低频子带系数采用基于区域空间频率的融合规则。双通道PCNN具有更简单的网络架构和更好的适应性。在大量的医学图像过程中,它耗时更少,并减少了计算复杂性。高频子带系数采用双通道PCNN融合规则。实验结果表明,与传统的融合方法相比,该方法可以大大提高融合图像的质量,并且耗时少,计算量少。

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