Image Defogging

Image defogging aims to computationally remove fog from images and videos, improving visibility and enabling better analysis in various applications like autonomous driving and medical imaging. Current research focuses on developing robust deep learning models, including generative adversarial networks (GANs) and transformer-based architectures, often trained on both synthetic and real-world datasets to enhance generalization. These advancements are driven by the need for improved accuracy, particularly in preserving image details and color fidelity, and the development of more realistic synthetic datasets for training and evaluation. The resulting improvements in image clarity have significant implications for computer vision tasks and applications requiring reliable visual information in challenging weather conditions.