Abstract: Ancient Chinese murals, with a history of thousands of years, inevitably have been damaged to varying
degrees, so the relevant restoration research is of great historical and cultural value. In the process of the traditional
manual restoration directly affecting the mural itself, improper operations will cause protective damages. Therefore,
digital virtual restoration was adopted, and a multi-scale mural restoration method based on edge reconstruction was
proposed. Due to the scarcity of existing murals, the experimental data was obtained by collecting and sorting out
different regions of Chinese murals. The freely cropped murals were filtered to smooth the image details and retain
their edges, which provided good initialization conditions for the image segmentation of damaged areas, then
automatic calculations were conducted on the mask to be repaired after image clustering. The repair process was based
on edge reconstruction, texture features of damaged murals were extracted in a multi-scale space, and the available
known information of the image was fully excavated to fill in its missing content. The experimental results show that the method is not limited by the type and degree of damages to the murals, the entire reconstruction process is more
versatile and effective, and it can recover images with complete structure and clear texture, and achieve better repair
results.

Key words: digital virtual repair, image filtering, segmentation model, image clustering, edge reconstruction;
multi-scale repair