Point Cloud Noise Reduction and Surface Reconstruction for Cultural Relics Digitization

Three-dimensional scanning technology has significantly advanced the digital preservation of cultural relics, providing a reliable means of safeguarding their physical and historical integrity. However, existing methods struggle to accommodate all characteristics of relics, particularly in cases involving complex structures or artifacts that cannot be physically handled. Further optimization is required in point cloud data processing techniques to enhance performance. To address this issue, this paper proposes a multiscale point cloud preprocessing and model reconstruction method tailored for the digitization of cultural relics. Various aspects of relic reconstruction are investigated, including point cloud denoising and model reconstruction, aiming to enhance denoising effects and improve the quality of relic reconstruction throughout the digitization process. The primary contributions of this paper are as follows: First, an optimized multiscale point cloud fusion denoising algorithm is applied to the collected point cloud data for denoising. Second, surface reconstruction of the point cloud is performed using two methods, followed by a comparative analysis of their effectiveness. Third, the reconstruction accuracy is analyzed to prove the reconstruction effect.