首页|伪对立学习与差分进化的改进鲸鱼优化算法及图像分割应用

伪对立学习与差分进化的改进鲸鱼优化算法及图像分割应用

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针对多阈值图像分割计算代价高、分割精度差的不足,提出伪对立学习与差分进化的改进鲸鱼优化最大熵多阈值图像分割算法.为了提升传统鲸鱼算法的寻优精度和收敛速率,引入伪对立学习和混沌Tent映射进行种群初始化,提升种群多样性和初始解质量,扩大精英个体对种群进化的引领作用;引入差分进化增强种群全局搜索能力,避免迭代后期陷入局部最优,进而实现改进算法O LDWOA.以最大熵函数评估适应度,利用O LD WOA对图像分割多阈值组合寻优,确定最优阈值.利用经典图像做图像分割实验,在计算效率、峰值信噪比、结构相似度和特征相似度指标上对比,证实该方法分割精度和分割效率优于同类算法.
IMPROVED WHALE OPTIMIZING ALGORITHM BASED ON PSEUDO OPPOSITION-LEARNING AND DIFFERENTIAL EVOLUTION AND APPLICATION OF IMAGE SEGMENTATION
Aimed at the shortcomings of high computation cost and poor accuracy of the multi-level thresholding image segmentation,an improved whale optimization maximal entropy threshold image segmentation algorithm based on differential evolution and pseudo opposition-learning is proposed.In order to improve the optimization precision and the convergence rate of traditional WO A,we introduced the pseudo opposition-learning and chaos Tent map to generate the initial population,which could promote the population diversity and the quality of initial solutions,and expand the leading effect of elite individuals.The differential evolution was applied to enhance the global search of the population,which could overcome the shortcoming of falling into a local optimum at later iterations.Based on these works we achieved an improved algorithm OLDWOA.Using the maximal entropy as fitness function,OLDWOA was applied to search the optimal multi-level threshold group of image segmentation,in order to determine the optimal segmentation thresholds.Using classic images to construct image segmentation experiments,we compared some index such as the computational efficiency,the peak signal-to-noise ratio(PSNR),the structural similarity(SSIM)and the feature similarity(FSIM).The obtained experimental results verify that our algorithm can obtain a higher segmentation accuracy and a higher segmentation efficiency than the same kind.

Image segmentationWhale optimization algorithmMaximal entropyDifferential evolutionPseudo opposition-learning

孙超

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重庆对外经贸学院大数据与智能工程学院 重庆 401520

图像分割 鲸鱼优化算法 最大熵 差分进化 伪对立学习

重庆市教委科学技术研究项目重庆对外经贸学院科学技术研究项目

KJQN201902002KYKJ202001

2024

计算机应用与软件
上海市计算技术研究所 上海计算机软件技术开发中心

计算机应用与软件

CSTPCD北大核心
影响因子:0.615
ISSN:1000-386X
年,卷(期):2024.41(9)