Zhang Xian-Shi, Yang Kai-Fu, Li Yong-Jie
Opt Express. 2021 May 24;29(11):16619-16638. doi: 10.1364/OE.423372.
Before being captured by observers, the information carried by light may be attenuated by the transmission medium. According to the atmospheric scattering model, this attenuation is wavelength-dependent and increases with distance. However, most existing haze removal methods ignore this wavelength dependency and therefore cannot handle well the color distortions caused by it. To solve this problem, we propose a scattering coefficient awareness method based on the image formation model. The proposed method first makes an initial transmission estimation by the dark channel prior and then calculates the scattering coefficient ratios based on the initial transmission map and the grey pixels in the image. After that, fine transmission maps in RGB channels are calculated from these ratios and compensated for in sky areas. A global correction is also applied to eliminate the color bias induced by the light source before the final output. Qualitatively and quantitatively compared on synthetic and real images against state-of-the-art methods, the proposed method provides better results for the scenes with either white fog or colorized haze.
在被观测者捕获之前，光所携带的信息可能会被传输介质衰减。根据大气散射模型，这种衰减与波长有关，并随距离增加。然而，大多数现有的去雾方法忽略了这种波长依赖性，因此无法很好地处理由此引起的颜色失真。为了解决这个问题，我们提出了一种基于图像形成模型的散射系数感知方法。该方法首先通过暗通道先验进行初始传输估计，然后根据初始传输图和图像中的灰色像素计算散射系数比率。之后，从这些比率计算出RGB通道中的精细传输图，并在天空区域进行补偿。在最终输出之前，还应用全局校正来消除光源引起的颜色偏差。在合成图像和真实图像上与现有方法进行定性和定量比较，该方法在有白雾或彩色雾霾的场景中都能提供更好的结果。
