Recent advances in image fusion technology in agriculture

Crop and livestock monitoring are essential for guiding agricultural production and improving agricultural yield by facilitating the early prevention and treatment of diseases, yield prediction, and automatic harvesting. However, traditional monitoring methods have some shortcomings, including by humans and through a single sensor, manual monitoring method is time-consuming and labor-intensive, monitoring methods using a single sensor are inaccurate. Therefore, research on improving the methods of crop and livestock monitoring is essential. Image fusion technology can help provide important information from two or more images that can be used to obtain comprehensive agricultural information. After discussing the advantages and disadvantages of various of image fusion methods in agriculture, this paper reviews the application of image fusion in crop recognition and detection, planting area estimation, plant diseases and pest detection, and livestock health assessment and classification. It also highlights the main challenges to the successful application of image fusion technology to agriculture, and discusses directions of future research and development directions in the area.

Automated summary

This article discusses the importance of crop and livestock monitoring in agricultural production, as well as the application of image fusion technology in improving monitoring methods. It reviews the specific applications of image fusion in areas such as crop recognition, disease detection, and livestock health assessment, while also highlighting the challenges and future research directions in the field.