基于IWOA-BP神经网络图像复原  

Image restoration based on IWOA-BP neural network

作　　者：何昌 詹道桦 周倍 罗志锋 黄仁彬 王晗[1] HE Chang;ZHAN Daohua;ZHOU Bei;LUO Zhifeng;HUANG Renbin;WANG Han(State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment,School of Mechanical and Electrical Engineering,Guangdong University of Technology,Guangzhou 510006,China)

机构地区：[1]广东工业大学机电工程学院,省部共建精密电子制造技术与装备国家重点实验室,广州510006

出　　处：《激光杂志》2024年第5期93-98,共6页Laser Journal

基　　金：广东省季华实验室项目(No.X190071UZ190);广东省自然科学基金资助(No.2021A1515011908)。

摘　　要：针对传统复原算法在退化图像复原过程中存在明显滞后的问题,建立了一种改进的鲸鱼算法(Improved Whale Optimization Algorithm,IWOA)-BP神经网络图像复原模型。首先,通过Tent混沌增强初始种群的均匀性和多样性;其次,采用非线性权重和改进的收敛因子,平衡算法的全局搜索与局部寻优能力;最后,结合Levy飞行策略更新个体位置,帮助算法跳出局部最优。随后采用经典图像数据,建立IWOA-BP模型。选取PSNR、SSIM和NMSE作为网络模型的评价指标,与BP、GWO-BP、WOA-BP进行对比。实验结果表明IWOA-BP模型图像复原视觉效果更好,提高了图像复原的质量。An Improved Whale Optimization Algorithm(IWOA)-BP neural network image restoration model was proposed to solve the problem of obvious lag in the process of restoring degraded images by traditional restoration algorithms.First,the uniformity and diversity of the initial population were enhanced by Tent chaos.Secondly,nonlinear weights and improved convergence factors are used to balance the global search and local optimization capabilities of the algorithm.Finally,the Levy flight strategy is combined to update the individual position to help the algorithm escape the local optimal.Then the IWOA-BP model is established by using the classical image data.PSNR,SSIM and NMSE were selected as the evaluation indexes of the network model,and compared with BP,GWO-BP and WOA-BP.The experimental results show that IWOA-BP model has better visual effect and improves the quality of image restoration.

关 键 词：图像复原 BP神经网络 Tent混沌 Levy飞行 改进的鲸鱼算法 

分 类 号：TN209[电子电信—物理电子学]