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基于暗通道先验的雾天车载图像增强算法研究

Improvement of Vehicle Image Enhancement Algorithm in Foggy Weather Based on Dark Channel Prior

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【作者】 钱宇清左付山叶健王海龙

【Author】 Qian Yuqing;Zuo Fushan;Ye Jian;Wang Hailong;College of Automobile and Traffic Engineering,Nanjing Forestry University;

【通讯作者】 左付山;

【机构】 南京林业大学汽车与交通工程学院

【摘要】 针对原始的暗通道先验去雾算法对天空及明亮区域处理时容易出现失真以及处理后图像偏灰暗的弊端,提出一种改进算法:基于暗通道先验估计大气光、利用阈值判断对天空区域透射率进行修正、使用直方图均衡化增强克服处理后图像偏灰暗。实验结果表明,改进算法提高了图像清晰度,同时还原了图像中更多的道路信息,弥补了传统暗通道算法的不足。

【Abstract】 In view of the disadvantages of the original dark channel a priori defogging algorithm,which is prone to distortion in the processing of the sky and bright areas and the gray image after processing,a method for estimating the atmospheric light based on the dark channel a priori is proposed,and the transmittance of the sky area is corrected by using the threshold judgment.Histogram equalization enhancement is used to overcome the disadvantage of gray image after processing.The experimental results show that the improved algorithm not only improves the image definition,but also restores more road information in the image,which makes up for the shortcomings of the traditional dark channel algorithm.

  • 【文献出处】 农业装备与车辆工程 ,Agricultural Equipment & Vehicle Engineering , 编辑部邮箱 ,2022年09期
  • 【分类号】U463.6;TP391.41
  • 【下载频次】214
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