As a powerful tool for active remote sensing of the atmosphere, lidar can be used to monitor the spatial and temporal distribution of clouds automatically and continuously. An improved cloud detection algorithm based on differential enhancement is proposed in this work. By introducing integral area and peak ratio algorithm, the improved algorithm cannot only effectively reduce the number of data fitting points during differentiation, improve the authenticity of cloud data, but also avoid misjudgment caused by strong noise points after differentiation in the traditional differential enhancing cloud detection algorithm. In addition, the improved algorithm also adds the merging of characteristic clouds, which can effectively reduce the mission caused by the traditional algorithm in the case of single-layer and multi-peak signals. Finally, the three kinds of simulated lidar signals and the measured Mie scattered lidar signals are used to analyze and compare the algorithms before and after the improvement. The results show that the improved algorithm maintains the superiority of cloud detection under the conditions of low signal-to-noise ratio, while further reduces the misjudgment and mission of characteristic clouds.