Sharp feature-preserving mesh denoising

Mesh denoising is a fundamental task in a geometry processing pipeline, where detail preservation is essential for several applications. In the case of objects that present sharp features, mesh denoising is challenging because smooth and sharp regions should be preserved simultaneously. In recent work, i.e. (Hurtado et al. 2022), a new sharp feature-preserving point cloud denoising method was proposed. This method is capable of dealing with both types of regions effectively. Although we can apply this method directly on the mesh vertices, it introduces several mesh artifacts because mesh topology is not taken into account. In this paper, we propose an extension of this method to deal correctly with triangle mesh data, introducing new steps that take advantage of the explicit topology defined by a mesh. These steps allow us to minimize the artifacts and obtain better-quality results. We compare this extended mesh denoising method with several state-of-the-art methods, showing that it is competitive and can be consistent through different test cases.