一种改进的透射率分布估计的夜间图像去雾算法

针对基于暗通道先验理论（dark channel prior, DCP）的去雾算法在处理夜间有雾图像时细节信息缺失、光源区域的纹理受损严重的问题，本文提出了一种改进的透射率分布估计的夜间图像去雾算法。通过引入暗态点光源模型、暗通道可信度权值因子和伪去雾图像，结合夜间图像成像模型，获取改进的透射率分布，对夜间降质图像进行去雾处理。实验结果表明，经本文算法处理后的图像在纹理细节上损失小、图像清晰度高，图像明暗对比度得到较好的拉伸，可以实现夜间有雾图像的有效去雾。

Nighttime Image Dehazing Algorithm Based on Improved Transmittance Distribution Estimation

This paper presents an improved transmittance distribution estimation algorithm for nighttime image dehazing to solve lack of detailed information and serious damage to the texture of light source areas when the dark channel prior dehazing algorithm processes foggy images at night. An improved transmittance distribution was obtained by introducing a dark state point light source model, a dark channel credibility weight factor, and a pseudo dehazing image, combined with a nighttime image imaging model, and the dehazed image at night was dehazed. The experimental results showed that the image processed by using the proposed algorithm had little loss in texture details and high image definition, and the contrast between the light and dark of the image was better stretched, which effectively dehazed a foggy image at night.