首页|Memristor-based multi-channel pulse coupled neural network for image fusion

Memristor-based multi-channel pulse coupled neural network for image fusion

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Image fusion is widely used in computer vision and image analysis.Considering that the traditional image fusion algorithm has a certain limitation in multi-channel image fusion,a memristor-based multi-channel pulse coupled neural network(M-MPCNN)for image fusion is proposed.Based on a dual-channel pulse coupled neural network(D-PCNN),a novel multi-channel pulse coupled neural network(M-PCNN)is firstly constructed in this paper.Then the exponential growth dynamic threshold model is used to improve the pulse generation of pulse coupled neural network,which can not only avoid multiple ignitions effectively,but can also improve operational efficiency and reduce complexity.At the same time,synchronous capture can also enhance image edge,which is more conducive to image fusion.Finally,the threshold and synaptic characteristics of pulse coupled neural networks(PCNNs)can be well realized by using a memristor-based pulse generator.Experimental results show that the proposed algorithm can fuse multi-source images more effectively than existing state-of-the-art fusion algorithms.

multi-channelmemristorpulse coupled neural network

Liu Jian、Wu Chengmao、Tian Xiaoping

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School of Electronic Engineering,Xi'an University of Posts and Telecommunications,Xi'an 710121,China

This work was supported by the National Natural Science Foundation of ChinaThis work was supported by the National Natural Science Foundation of ChinaShaanxi Natural Science Foundation of ChinaShaanxi Natural Science Foundation of China

61671377517092282016JM80342017JM6107

2020

10.19682/j.cnki.1005-8885.2021.0046

中国邮电高校学报(英文版)
北京邮电大学

中国邮电高校学报(英文版)

CSCDEI
影响因子：0.419
ISSN：1005-8885
年,卷(期)：2020.27(6)
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