基于改进大气光估计的单幅机场图像去雾
Improved Atmospheric Light Estimation for Single Airport Image Dehazing
周睿 1孟双杰 1李明 1邱爽1
作者信息
- 1. 中国民用航空飞行学院空中交通管理学院,四川 广汉 618307
- 折叠
摘要
为提高机场监视系统在大雾天气的可靠性,提出了一种面向机场图像去雾的大气光值估计方法.首先,该方法基于暗通道先验(DCP)估计大气透射率,利用标准大气散射模型还原初始去雾图像;然后,引入清晰度系数来公式化图像去雾输出的反馈,在此基础上设计了一种大气光值更新规则,利用图像去雾输出的反馈来迭代更新大气光值,直至清晰度系数达到峰值便停止更新;最后,在更新后的大气光值引导下,利用大气散射模型重建出最优无雾图像.实验结果表明,相较于传统DCP方法,所提方法可以得到更准确的大气光值估计和更自然的去雾图像,在图像去雾客观评价指标上表现得更好.
Abstract
To enhance the reliability of airport surveillance systems during heavy fog,this paper proposes a method to estimate atmospheric light values for airport images dehazing.First,the method estimates the atmospheric transmittance based on the dark channel prior(DCP)and applies a standard atmospheric scattering model to restore the initial dehazed image.Second,the clarity coefficient is introduced to provide feedback on the dehazed image.Based on this feedback,a rule is designed to iteratively update the atmospheric light value,adjusting it until the clarity coefficient peaks.Finally,guided by the updated atmospheric light value,the atmospheric scattering model reconstructs the optimal fog-free image.Experimental results demonstrate that,compared with traditional DCP method,the proposed method achieves more accurate atmospheric light values,resulting in more natural dehazing and outperforming existing objective evaluation indices for image dehazing.
关键词
大气散射模型/大气光值估计/暗通道先验/图像去雾Key words
atmospheric scattering model/atmospheric light value estimation/dark channel prior/image dehazing引用本文复制引用
出版年
2024
NETL
NSTL
万方数据