Description
Denoise your mesh Mesh models generated by 3D scanner always contain noise. It is necessary to remove the noise from the meshes. Mesh denoising: remove noises, feature-preserving https://www.cs.cf.ac.uk/meshfiltering/index_files/Doc/Random%20Walks%20for%20Mesh%20Denoising.ppt
settings
| Name | Description |
|---|---|
| input | Input Mesh (OBJ file format) |
| Denoising Iterations | Number of denoising iterations (0 - 30) |
| Mesh Update Closeness Weight | Closeness weight for mesh update, must be positive(0 - 0.1) (0.001) |
| Lambda | Regularization weight. (0.0 // 10.0 // 0.01) 2 |
| Eta | Gaussian standard deviation for spatial weight, scaled by the average distance between adjacent face centroids. Must be positive.(0.0 - 20) (1.5) |
| Gaussian standard deviation for guidance weight (0.0-10) (1.5) | |
| Gaussian standard deviation for signal weight. (0.0-5) (0.3) | |
| Mesh Update Mesh | Mesh Update Method * ITERATIVEUPDATE (default): ShapeUp styled iterative solver * POISSONUPDATE: Poisson-based update from [Wang et al. 2015] (0, 1) |
| Verbose Level | ['fatal', 'error', 'warning', 'info', 'debug', 'trace'] |
| Output | Output mesh (OBJ file format). |
Mesh Update Method https://www.researchgate.net/publication/275104101_Poisson-driven_seamless_completion_of_triangular_meshes
Wang et al. https://dl.acm.org/citation.cfm?id=2818068
Detailed Description
A larger value of Lambda or Eta leads to a smoother filtering result.
From: "Static/Dynamic Filtering for Mesh Geometry" by Zhang Et al. https://arxiv.org/pdf/1712.03574.pdf