Image Degradation

Image degradation encompasses the various processes that reduce the quality of images, hindering their use in applications ranging from medical diagnosis to autonomous driving. Current research focuses on developing robust and efficient image restoration methods, often employing deep learning architectures like GANs, diffusion models, and transformers, to handle multiple degradation types simultaneously and adapt to unseen degradations. These advancements are crucial for improving the reliability and accuracy of image-based systems across numerous fields, particularly where image quality is critical for decision-making.