采用暗态点光源模型的夜间去雾算法

针对夜间雾、霾场景下的去雾图像存在颜色失真、纹理损失、亮度低等缺陷，本文提出了一种采用暗态点光源模型的夜间去雾算法，通过构建夜间雾、霾场景的暗态点光源模型，利用联合双边滤波、限制对比度自适应直方图均衡化等算法对降质图像进行处理，结合大气散射模型得到去雾图像。实验结果表明，该算法的处理速度快、夜间去雾效果较好，较对比算法在对比度、平均梯度以及信息熵上均有一定程度地改善，有效解决了去雾图像的颜色失真、纹理损失、亮度低等缺陷。

Nighttime Fog Removal Using the Dark Point Light Source Model

To address image distortion, texture loss, and low brightness in nighttime fog scenes, this paper proposes a nighttime defogging algorithm based on a dark point light source model. The dark point light source model was first constructed and the degraded image was processed by an algorithm that utilizes both bilateral filtering and limited contrast adaptive histogram equalization. Then, the defogging image was obtained by combining with the atmospheric scattering model. The experimental results show that this algorithm has a fast processing speed, a better effect of nighttime fogging, and a certain degree of improvement in terms of contrast, average gradient, and information entropy when compared with the contrast algorithm. This model can therefore effectively address image distortion, texture loss, and low brightness of fogging images.