Structure-guided virtual restoration for defective silk cultural relics

The digital restoration of damaged silk relics is a type of blind restoration problem that relies on limited prior information. Existing image restoration techniques face significant difficulties in repainting missing patterns of both structural and content. Silk cultural relics are prone to decay, mold, moth, fading, pollution, and adhesion due to long-term exposure to external factors such as temperature, humidity, and microorganisms. Thus, restoring cultural relic patterns is crucial for archeological and design industries. Virtual restoration, based on image inpainting technology, can tackle this problem. However, existing inpainting algorithms are not effective in defective areas lacking a structural trend and only relying on prior information. Moreover, the unique and irregular patterns of silk cultural relics pose a further challenge. To address these issues, we propose a structure-guided virtual restoration method. Concretely, to maintain global image consistency, we introduce an adaptive curve fitting algorithm to reconstruct missing structural lines. We then establish a new priority function to improve the filling order of patches to be repaired, and an adaptive selection of the sample block size is adopted based on the sparsity of the structure. Our method outperforms existing techniques by reconstructing the structural lines according to the pattern design, thus guiding image inpainting to avoid erroneous fillings and block effects. Results show that the restored images achieved an average SSIM of 0.977 and an average PSNR of 39.16. The proposed method for virtual restoration, utilizing curve fitting and image inpainting guided by the artifact's structure, has demonstrated significant improvements in the preservation of structure continuity and faithful reproduction of original patterns on the silk cultural relics.