摘要
该文提出一种改进的基于去雾理论的夜间低照度图像增强算法。通过对暗通道先验去雾算法在处理夜间复杂灯光图像中存在的伪光晕、亮度不准等问题进行分析,采用一种可以边缘保持的滤波方法进行暗通道求取,并针对图像特点对大气光值进行精确估计,结合采样方法提升处理效率,实现对低照度图像的有效增强。经过实验分析,该算法能有效地防止光晕现象,改善图像的亮度和噪声。
In this paper,an improved night low illuminance image enhancement algorithm based on defog theory is proposed.Based on the analysis of the problems of false halo and inaccuracy of brightness in the dark channel prior defogging algorithm in dealing with the complex light image at night,a filtering method which can preserve the edge is used to calculate the dark channel.According to the characteristics of the image,the atmospheric light value is accurately estimated,combined with the sampling method to improve the processing efficiency,and realize the effective enhancement of the low illumination image.Through experimental analysis,the algorithm can effectively prevent the halo phenomenon and improve the brightness and noise of the image.
作者
庞明
鞠金宝
PANG Ming;JU Jinbao
出处
《科技创新与应用》
2023年第31期36-41,共6页
Technology Innovation and Application
关键词
海面复杂背景
图像增强
低照度
图像去噪
暗通道先验
sea surface complex background
image enhancement
low illuminance
image denoising
dark channel priori
