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The aim is to develop a diffusion model that enhances the digital restoration of damaged Dunhuang murals.

May 9, 2026npj Heritage ScienceOpen Access

DMEA-Net: a diffusion-based network for mural image restoration using enhanced multi-head contextual attention

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The aim is to develop a diffusion model that enhances the digital restoration of damaged Dunhuang murals.
Proposed a novel diffusion model with an Enhanced Multi-head Contextual Attention (EMCA) strategy.
Focused on capturing complex features and multi-scale information in mural restoration.
Evaluated performance on datasets of damaged murals categorized into cracks, peeling, and fading.
Demonstrated significant improvements in PSNR, SSIM, and LPIPS metrics compared to baseline methods.
Achieved clearer outputs and enhanced visual effects in mural restoration.

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Randomized trial shows improved restoration accuracy of damaged murals, highlighting digital recovery's potential.

Li et al. (2026) studied this question.

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