Optimization of Digital Inheritance Pathway of Folk Art in Information Age

Abstract

How to make full use of digital information technology to realize the digital heritage of folk art has become a key concern in the field of non-legacy. Based on digital information technology, this paper proposes image restoration technology to assist folk art digital heritage research. Folk art images are acquired by double mirror reflection method, and pre-processing operations such as defogging, denoising and edge detection are carried out on the images to reduce the influence of interference information in the original pictures on the image restoration effect. The Criminisi algorithm is improved and optimized by combining the structure tensor theory, the improved priority calculation function, the matching criterion and the confidence updating method, and then the research design of image restoration technology assisting folk art digitization is completed and analyzed by examples. The results show that the repair effect of the improved Criminisi algorithm is better than that of the classical Criminisi algorithm, but the repair time of the improved Criminisi algorithm is longer than that of the traditional algorithm by 64.25%, but it is still less than 0.500 seconds, which is within the acceptable range, and it has certain practicability for the digitization and inheritance of folk art in the information age. algorithm has some practicality. Compared with other digital inheritance paths, the method proposed in this study can restore the original appearance of folk art to the maximum extent, and it has theoretical guidance value for the study of optimizing the digital inheritance of traditional folk art.