Noise Transparentization Approach for High-Precision Visualization of 3D Scanned Point Clouds

A point-based deep peeling method applicable to processing three-dimensional (3D) scanned point clouds is proposed in this paper, which has been originally used in the field of polygon processing. With this method, the task of photorealistic, i.e., opaque visualization of a 3D scanned point cloud, is achieved by extracting visible points and making noise points transparent, i.e., invisible. Additionally, this method does not result in loss of clarity and can finely visualize the detailed structure of the object. It allows the method to achieve high-precision visualization of 3D scanned point clouds. By taking advantage of the low color stability of the noise, our method ensures that the visualized object itself is made opaque and visible while the noise points are made invisible. The effectiveness of transparentizing noise is demonstrated using actual 3D scanned point cloud data for a high-value cultural heritage object, and the proposed method may be a ideal solution of opaque visualization of 3D scanned point clouds.