基于变异鸡群优化透射率估计的去雾算法  

Image Dehazing Based on Transmittance Estimation by Variant Chicken Swarm Optimization Algorithm

作　　者：吴龙[1] 陈杰[1] 陈淑玉 杨旭[1] 徐璐[1] WU Long;CHEN Jie;CHEN Shuyu;YANG Xu;XU Lu(School of Computer Science and Technology,Zhejiang Sci-Tech University,Hangzhou 310018,China;Keyi College,Zhejiang Sci-Tech University,Shaoxing 312369,China)

机构地区：[1]浙江理工大学计算机科学与技术学院,浙江杭州310018 [2]浙江理工大学科技与艺术学院,浙江绍兴312369

出　　处：《电子科技》2024年第11期22-30,共9页Electronic Science and Technology

基　　金：国家自然科学基金(61801429);浙江省自然科学基金(LY20F010001,LQ20F050010);浙江理工大学基本科研业务费专项资金(2021Q030)。

摘　　要：在大雾天气下,收集的图片存在清晰度降低和颜色畸变等问题。为获得高质量的去雾图像,文中提出了一种混合暗通道去雾算法。该算法使用Retinex算法去除照射分量的干扰,采用变异鸡群优化算法获得引导滤波所需的导向图片来优化大气透射率,并应用改进的暗通道先验算法来获得去雾图像。相较于其他暗通道先验去雾算法,该方法的平均标准差降低了28.3%,平均峰值信噪比增长了10.3%,平均熵增加了8.0%。测试了同一个场景中不同雾霾程度下的图片,结果显示图片清晰,细节信息保留完整,且评价标准数值基本保持稳定。测试结果表明,所提算法具有较高的鲁棒性和良好的色彩保真能力。In foggy weather,the collected pictures have the problems of reduced clarity and color distortion.In order to obtain haze-free images with high quality,a hybrid dark channel prior algorithm is proposed in this study.The proposed algorithm employs Retinex algorithm to remove the interference of the illumination component.The variant chicken swarm optimization algorithm is used to obtain the guidance image required by the guided filter to optimize the atmospheric transmittance.The improved dark channel prior algorithm is used to obtain the fog removal image.Compared with other dark channel prior defogging algorithms,the mean standard deviation of the proposed method is reduced by 28.3%,the mean peak signal-to-noise ratio is increased by 10.3%and the mean entropy is increased by 8.0%.In this study,the pictures of different haze levels under the same scene are tested.The results show that the pictures are clear,the details are intact,and the evaluation standard values are basically stable.The above test results indicate that the proposed algorithm has high robustness and color fidelity capabilities.

关 键 词：图像去雾 混合暗通道先验算法 变异鸡群优化算法 透射率 大气光强 RETINEX 大气散射模型 引导滤波 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]