Name
Abstract | ||
|---|---|---|
We propose a 3D anisotropic diffusion filter for denoising and enhancing oriented data. The approach is a generalization of a previous contribution and it is based on a novel, more precise orientation estimation step. The orientation in the 3D space is computed using an asymmetric Isotropic Recursive Oriented Network (IRON) operator that can handle in a natural way junctions and corners. In the experimental section we employ a set of 3D synthetic blocks to illustrate the efficiency of the new method through quantitative and visual comparisons with other 3D-extended classical models or recently proposed 3D Partial Differential Equations (PDE). |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1117/12.838742 | Proceedings of SPIE |
Keywords | Field | DocType |
3D filtering,IRON orientation estimation,directional derivative,anisotropic diffusion | Noise reduction,Anisotropic diffusion,Isotropy,Mathematical analysis,Image processing,Operator (computer programming),Artificial intelligence,Directional derivative,Recursion,Computer vision,Mathematical optimization,Partial differential equation,Physics | Conference |
Volume | ISSN | Citations |
7526 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 4 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sorin Pop | 1 | 27 | 3.02 |
| Romulus Terebes | 2 | 49 | 8.42 |
| Jean Pierre Da Costa | 3 | 66 | 7.09 |
| Christian Germain | 4 | 113 | 18.95 |
| Monica Borda | 5 | 63 | 13.54 |
| Cosmin Ludusan | 6 | 11 | 1.30 |
| Olivier Lavialle | 7 | 72 | 9.51 |