Cloud Removal

Cloud removal from satellite and other imagery aims to reconstruct clear views of the Earth's surface obscured by clouds, improving the quality and usability of remote sensing data. Current research heavily utilizes deep learning, particularly diffusion models and convolutional neural networks (CNNs), often incorporating multi-modal data fusion (e.g., combining optical and radar imagery) and attention mechanisms to enhance accuracy and detail recovery. These advancements are crucial for various applications, including improved weather forecasting, precision agriculture, and environmental monitoring, by providing more complete and reliable datasets for analysis.