Literature Review on Image Restoration

Abstract

Image restoration is an essential part in the field of computer vision, which aims at predicting and filling the pixels of the missing images to achieve satisfactory visual effects, it has extensive application value in the fields of film and television special effects production, image editing, digital cultural heritage protection and virtual reality. With the introduction and application of the concept of deep learning in recent years, it has been widely studied in the academic and industrial fields, the performance of image restoration has been significantly improved, so that this long-standing research topic has once again aroused widespread concern and heated discussion on the social level. In order to enable more researchers to explore the theory of image restoration and its development, this paper reviews the related technologies in this field: firstly, the traditional image restoration methods are described, secondly, the background of deep learning is introduced, then the image restoration methods based on deep learning are described, subsequently, the several deep-learning based methods are compared and analyzed, finally, the future research direction and emphasis of image restoration are analyzed and prospected.