GLHMS算法的PCNN参数优化及其在图像融合中的应用  

Optimization of PCNN Parameters of GLHMS Algorithm and Its Application in Image Fusion

作　　者：徐仵博 刘立群[1] XU Wubo;LIU Liqun(College of Information Science and Technology,Gansu Agricultural University,Lanzhou 730070,China)

机构地区：[1]甘肃农业大学信息科学技术学院,甘肃兰州730070

出　　处：《软件导刊》2023年第8期187-195,共9页Software Guide

基　　金：甘肃省高校教师创新基金项目(2023A-051);甘肃农业大学青年导师基金项目(GAU-QDFC-2020-08);甘肃省科技计划项目(20JR5RA032)。

摘　　要：人类心理搜索算法(HMS)和脉冲耦合神经网络(PCNN)存在收敛精度低、参数太多等问题,导致融合图像质量不高,由此提出一种基于参数自适应的PCNN图像融合方法。首先,将均匀分组、局部搜索以及移动次数算子引入人类心理搜索算法,克服了HMS存在的搜索能力不强、收敛速度慢等问题;然后,通过改进后的算法对PCNN的αθ、β、αL 3个参数进行优化,增强了其特征提取性能;最后,通过参数优化后的PCNN融合ToF和RGB图像,得到完整的融合图像。选取20个测试函数对算法进行仿真实验,结果表明,算法能够有效地加快收敛速度,提高寻优精度。选取不同时间光线下的果园图像验证了该方法的有效性,平均指标相较于DWT、TIF、CNN、PCNN、DWT_PCNN分别提高19.99%、30.74%、21.14%、17.6%、8.93%,能显著提高融合图像质量。Aimed at the problems of low convergence accuracy and too many parameters of human mental search algorithm and pulse coupled neural network,which lead to poor quality of fused images,a PCNN image fusion method based on parameter adaptation is proposed.First,an algorithm that introduces uniform grouping,local search and the move count operator into the human mental search algorithm is proposed to overcome the problems of poor search ability and slow convergence of HMS;Then,the PCNN'sαθ,β,αL parameters are optimized by the im⁃proved algorithm to enhance its feature extraction performance;Finally,the complete fused image is obtained by fusing the ToF and RGB im⁃ages with the PCNN after parameter optimization.Twenty test functions were selected for simulation experiments of the algorithm,and the ex⁃perimental results showed that the proposed algorithm can effectively speed up the convergence speed and improve the accuracy of the optimi⁃zation search.The effectiveness of the method was verified by selecting orchard images under different temporal lighting,and the average index of the proposed method was improved by 19.99%,30.74%,21.14%,17.6%,and 8.93%compared to DWT,TIF,CNN,PCNN,and DWT_PCNN,respectively.The method can significantly improve the quality of fused images.

关 键 词：人类心理搜索算法 脉冲耦合神经网络 图像融合 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]