科技创新与应用2024，Vol.14Issue(20)：1-7,7.DOI:10.19981/j.CN23-1581/G3.2024.20.001
基于遗传蚁群优化的PCNN改进中值滤波图像去噪方法
朱雪梅1
作者信息
- 1. 四川省内江市中心血站,四川 内江 641099
- 折叠
摘要
Abstract
In order to realize adaptive image denoising,animproved pulse coupled neural network(PCNN)median filter image denoising method based on genetic ant colony algorithm(GACA)is proposed.Through the combination of genetic algorithm(GA)and ant colony optimization(ACO)algorithm,the calculation results of GA are used to enhance the early pheromones of ACO,and finally make ACO accelerate the optimization of the key parameters of PCNN in the positive feedback mechanism;then,PCNN was used to optimizemedian filtering technology for image denoising.Through experimental analysis and quantitative calculation,as well as comparison with other existing image denoising techniques,the results show that the proposed GACA-MF improved hybrid image denoising method is better than using median filtering algorithm and PCNN algorithm respectively.It can be seen that using adaptive way to optimize network parameters can explore the maximum potential of PCNN as much as possible.关键词
图像去噪/遗传蚁群算法/脉冲耦合神经网络/中值滤波/优化参数Key words
image denoising/genetic ant colony algorithm/pulse coupled neural network(PCNN)/median filtering/Optimize parameters分类
信息技术与安全科学引用本文复制引用
朱雪梅..基于遗传蚁群优化的PCNN改进中值滤波图像去噪方法[J].科技创新与应用,2024,14(20):1-7,7.
