Yunnan Ancient Mural Restoration Based on Deep Learning

Abstract

Image restoration is an important part of the research in the field of computer vision. Its purpose is to automatically recover lost content based on known content in mural images, in mural image editing, film and television special effects production, virtual reality and digital cultural heritage protection. The field has a wide range of application values. In the method of image restoration based on deep learning, the design of the deep learning network and the selection of the loss function in the training process are important contents. Each method has its own advantages and disadvantages and its scope of application. How to improve the semantics of the repair result? The correctness of sex, structure and detail has always been the direction of researchers’ efforts. Based on this purpose, this paper summarizes the main features, existing problems, requirements of training samples, main application fields and references through various methods. Code. Based on the research of deep learning mural image restoration, some significant progress has been made. However, the application of deep learning in mural image restoration is still in its infancy. The main research content is only the mural image content information of the mural image itself to be repaired. Therefore, the restoration of mural image based on deep learning is still a challenging subject. How to design a universal repair network to improve the accuracy of the repair results requires more in-depth research.