Mesh denoising by improved 3D geometric bilateral filter

We present an improved mesh denoising method based on 3D geometric bilateral filtering. Its novelty is that it can preserve the details of the object as well as reduce the noise in an effective manner. The previous approach of geometric bilateral filtering for 3D-scan points has a limitation that it reduces the point density, thereby losing the details present in the object. The approach proposed by us, on the contrary, works on the surface mesh obtained after triangulating the 3D-scan points without any data downsampling. Each vertex of the mesh is repositioned appropriately based on the estimated centroid of the vertices in its local neighborhood and a Gaussian weight function. Experimental results demonstrate its strength, efficiency, and robustness.