梯度法、标准偏差法只能反演单一时刻的大气边界层高度，为此，提出了一种可以反演一段时间内大气边界层高度的图像边缘检测法。通过对常规方法的介绍和分析，说明研究图像边缘检测法的必要性。利用自主研发的激光雷达实测数据进行反演分析了一个昼夜和4种不同天气背景下的大气边界层高度，图像边缘检测方法与梯度法和标准偏差法反演大气边界层高度的均方根误差最小值为9.4 m和11.4 m。实验结果表明，该方法简单可靠、准确性高、不需要选取初始值，与传统常规方法相比具有更低的敏感性和更强的自适应性。

The gradient method and standard deviation method are only the inversion of the atmospheric boundary layer height of the single moment. For this issue, an image edge detection method is presented using retrieve the height of atmospheric boundary layer over a period of time. Through the introduction and analysis of the conventional method, the necessity of the research on image edge detection is illustrated. The atmospheric boundary layer height of a day and night and four kinds of different weather backgrounds are analyzed by using the independent research and development lidar to measure real-time data. The minimum root mean square errors of the image edge detection method with the gradient method and the standard deviation method for the inversion of the atmospheric boundary layer height are 9.4 m and 11.4 m, respectively. Experimental results show that the proposed algorithm is simple, reliable and high accuracy, and there is no need to choose the initial value, which has lower sensitivity and stronger adaptability than the traditional methods.