Abstract

Haze often degrades the contrast and limits the visibility of scenes, and as a result it has a negative impact on the safe driving of intelligent vehicles. In order to solve this problem and enhance the quality of hazy images, this paper proposes an improved single image haze removal method. The main works include two parts. On the one hand, an improved atmospheric light estimation method is addressed to achieve an accurate estimation of the atmospheric light. On the other hand, the transmission map is refined with a composite filter using bilateral one followed by adaptive parameter adjustment on the transmission function. The experimental results show that the presented approach can obtain substantial improvements on the color and the detail recovery on both synthetic and real-world datasets.

中文翻译：

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改进的单图像除雾功能，可实现智能驾驶

摘要

雾度通常会降低对比度并限制场景的可见性，因此对智能车辆的安全驾驶产生负面影响。为了解决该问题并提高模糊图像的质量，提出了一种改进的单图像雾度去除方法。主要工作包括两个部分。一方面，提出了一种改进的大气光估计方法，以实现对大气光的精确估计。另一方面，通过使用双边滤波器的复合滤波器完善传输图，然后对传输函数进行自适应参数调整。实验结果表明，该方法可以在合成数据集和真实数据集上显着改善颜色并改善细节恢复。