SAR Image

Synthetic Aperture Radar (SAR) images, generated by transmitting and receiving microwave signals, provide valuable all-weather, day-night remote sensing data. Current research focuses on improving SAR image quality through techniques like denoising (e.g., using temporal filtering and adaptive methods), synthesis (leveraging diffusion models and neural radiance fields), and accurate simulation (incorporating physics-based models and differentiable ray tracing). These advancements are crucial for applications ranging from flood detection and deforestation monitoring to target classification and improved understanding of ocean surface dynamics, ultimately enhancing the utility of SAR data across diverse scientific disciplines and practical applications.