Weather Image Restoration

Weather image restoration aims to computationally remove weather-related degradations (rain, snow, haze) from images, improving clarity and enabling reliable analysis in applications like autonomous driving. Current research focuses on handling multiple simultaneous weather conditions and improving generalization to unseen weather types, employing transformer-based architectures, diffusion models, and techniques like prompt learning and meta-learning to achieve this. These advancements are crucial for enhancing the robustness and accuracy of computer vision systems operating in challenging real-world environments.