Haze removal is important for computational photography and computer vision
applications. However, most of the existing methods for dehazing are designed
for daytime images, and cannot always work well in the nighttime. Different
from the imaging conditions in the daytime, images captured in nighttime haze
condition may suffer from non-uniform illumination due to artificial light
sources, which exhibit low brightness/contrast and color distortion. In this
paper, we present a new nighttime hazy imaging model that takes into account
both the non-uniform illumination from artificial light sources and the
scattering and attenuation effects of haze. Accordingly, we propose an
efficient dehazing algorithm for nighttime hazy images. The proposed algorithm
includes three sequential steps. i) It enhances the overall brightness by
performing a gamma correction step after estimating the illumination from the
original image. ii) Then it achieves a color-balance result by performing a
color correction step after estimating the color characteristics of the
incident light. iii) Finally, it remove the haze effect by applying the dark
channel prior and estimating the point-wise environmental light based on the
previous illumination-balance result. Experimental results show that the
proposed algorithm can achieve illumination-balance and haze-free results with
good color rendition ability.

提出了一种新的夜间雾天成像模型和高效的消除夜间雾天影响的算法，包括三个步骤：整体亮度增强，色彩平衡和去除雾效应。实验结果表明，该算法可以实现良好的颜色再现能力。