针对雾天条件下成像设备采集到的图像目标主体不清晰，细节信息不明显，可辨识度低等问题，提出了一种基于光幕约束和分段调整的图像去雾算法。首先将大气光幕的基本不等条件映射至正方形及其内切圆平面模型中，得到约束后的初始大气光幕；然后利用饱和度逼近构造粗糙大气光幕，以模糊无用的边缘信息，并通过梯度约束求取边缘代价对初始大气光幕进行修正。为了改善近景失真和远景去雾不彻底，建立自适应分段调整函数对大气光幕进行优化；最后通过复原模块得到清晰图像。实验结果表明：与一些经典的去雾算法相比，所提算法可以应用于各类图像，去雾效果良好，不仅保留了原图像特性而且得到的复原图像色彩明亮，清晰自然，各项指标优势明显。

Aiming at these problems of unclear targets， unobvious details， and lower resolution of images captured by imaging equipment under foggy conditions， an image dehazing algorithm based on atmospheric veil constraints and piecewise adjustment was proposed. Firstly， basic unequal relation of the atmospheric veil was mapped to plane model of square and its inscribed circle to obtain the constrained initial atmospheric veil. Then saturation approximation was used to get a rough atmospheric veil to blur the edge information. Meanwhile， gradient constraint was also introduced to detect the edge cost， which was utilized to correct initial atmospheric veil. In order to improve the distortion of images with close region and the incomplete defogging of images with distant region， an adaptive piecewise adjustment function was proposed to optimize the atmospheric veil. Finally， a clear image was obtained by the restoration module. Experimental results show that the proposed algorithm can be applied to all kinds of images， and has better defogging effect compared to some classic algorithms。It not only maintains the original images'characteristics， but also obtains the restored image with bright， clear and natural colors， and has advantages in various indicators.