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Research on Ancient Mural Diffusion Generative Inpainting Algorithm Based on Structure-Guided
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Yong CHEN1, 2, Shilong ZHANG1, Wanjun DU1, Zhixin FAN1
Journal of Beijing University of Posts and Telecommunications | 2025, 48(5) : 144 - 150
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Journal of Beijing University of Posts and Telecommunications | 2025, 48(5): 144-150
• REPORTS •
Research on Ancient Mural Diffusion Generative Inpainting Algorithm Based on Structure-Guided
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Yong CHEN1, 2, Shilong ZHANG1, Wanjun DU1, Zhixin FAN1
Affiliations
  • 1.School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
  • 2.Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics and Image Processing, Lanzhou Jiaotong University, Lanzhou 730070, China
doi: 10.13190/j.jbupt.2024-174
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Aiming at the problems of inadequate utilization of structural semantics and poor repair results of detailed features in the existing deep learning methods for repairing ancient murals, a structure-guided diffusion generative algorithm was proposed. Firstly, a mural structure reconstruction module composed of gated convolution and fast Fourier residual block is constructed, and the edge structure after reconstruction is used to guide the repair of damaged murals, so as to overcome the problem of insufficient utilization of structural semantic repair. Then, a generative diffusion module based on stochastic differential equation is proposed, which performs forward diffusion processing on the mural image to be repaired by stochastic differential equation. Next, a mask-enhanced backward iterative reconstruction module is designed to enhance the semantic consistency between the damaged area and the intact area of the mural, and improve the repair ability of the detailed features of the mural. Finally, the digital inpainting experiments and analysis are carried out on the Dunhuang mural data set. The experimental results show that the proposed algorithm can effectively complete the mural restoration, and the objective evaluation indicators are better than the comparison algorithms.

mural inpainting  /  diffusion modeling  /  structural guidance  /  mask enhancement  /  generative inpainting
Yong CHEN, Shilong ZHANG, Wanjun DU, Zhixin FAN. Research on Ancient Mural Diffusion Generative Inpainting Algorithm Based on Structure-Guided[J]. Journal of Beijing University of Posts and Telecommunications, 2025 , 48 (5) : 144 -150 . DOI: 10.13190/j.jbupt.2024-174
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doi: 10.13190/j.jbupt.2024-174
  • Receive Date：2024-09-06
  • Online Date：2026-04-16
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  • Received：2024-09-06
Affiliations
    1.School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
    2.Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics and Image Processing, Lanzhou Jiaotong University, Lanzhou 730070, China
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