Abstract: Restoration of degraded image is an important and challenging issue in the field of image computing. In recent years, artificial intelligence (AI), especially deep learning, has achieved rapid progress. More and more methods based on neural networks have been proposed to solve this problem. This paper first introduces the main techniques based on neural networks to restore the degraded images and makes a classification of the problems. Then we focused on the key neural networks to resolve the problems of each category. By reviewing the development of various network-based methods in the field of deep learning, we analyzed the advantages and limitations between these methods. Furthermore, a comparison between these methods and the traditional ones was also made. Finally, we put forward a new solution on restoration of extremely degraded image using GANs, sketching out the future work on the restoration of degraded image.

Key words: degraded image restoration, neural network, generative adversarial networks, artificial intelligence