Research on Application and Algorithm Optimization of UAV in Agricultural Monitoring

With the rapid development of UAV technology, its application in agriculture has been paid more and more attention. UAV can be equipped with multi-spectral and hyperspectral cameras to monitor farmland with high precision and obtain key information such as crop growth, soil moisture, pests and diseases in real time. However, UAV faces challenges in agricultural monitoring, such as flight stability, endurance, data acquisition and processing speed. Therefore, this study uses Phantom 4 RTKUAV in DJI for agricultural monitoring, and optimizes the image preprocessing algorithm. Noise is removed by median filtering algorithm, and image edge information is retained. The histogram equalization method is used to enhance the contrast and clarity of the image. The experimental results show that the optimized algorithm can significantly improve the image quality and improve the accuracy and efficiency of data processing. In addition, the importance of parameter selection of the algorithm is discussed, and suggestions for future research are put forward.