Name
Abstract | ||
|---|---|---|
This article proposes a novel 3D diffusion approach to filter oriented patterns. This approach was first developed to denoise and enhance seismic 3D data composed of a stack of layers disturbed by noise and broken by faults. The proposed filter is an extension of a 2D filter based on a classical diffusion equation including also additional orientation information. Considering 3D structures containing oriented planes, we search at each pixel the orientation of the tangential plane. The mean orientation information is included in the classical diffusion equation; the diffusion is steered at each pixel according to the directional tendency. Through some results on synthesized 3D blocks we will show that our method is able to eliminate noise while keeping edges and transitions. |
Year | Venue | Keywords |
|---|---|---|
2004 | EUSIPCO | nonlinear filters,2d filter,3d diffusion,diffusion equation,seismic 3d data,tangential diffusion,tangential plane |
Field | DocType | ISBN |
Anisotropic diffusion,Computer vision,Mathematical analysis,Pixel,Artificial intelligence,Diffusion equation,Mathematics | Conference | 978-320-0001-65-7 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Regis Dargent | 1 | 0 | 0.34 |
| Romulus Terebes | 2 | 49 | 8.42 |
| Olivier Lavialle | 3 | 72 | 9.51 |
| Pierre Baylou | 4 | 139 | 21.74 |