Name
Abstract | ||
|---|---|---|
This work revisits the Shock Filters of Osher and Rudin [OR90] and shows how the proposed filtering process can be interpreted as the advection of image values along flow-lines. Using this interpretation, we obtain an efficient implementation that only requires tracing flow-lines and re-sampling the image. We show that the approach is stable, allowing the use of arbitrarily large time steps without requiring a linear solve. Furthermore, we demonstrate the robustness of the approach by extending it to the processing of signals on meshes in 3D. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1111/cgf.12708 | Computer Graphics Forum |
Field | DocType | Volume |
Computer vision,Polygon mesh,Computer science,Geometry processing,Image processing,Filter (signal processing),Robustness (computer science),Theoretical computer science,Artificial intelligence,Tracing,Arbitrarily large,Cognitive neuroscience of visual object recognition | Journal | 34 |
Issue | ISSN | Citations |
5 | 0167-7055 | 4 |
PageRank | References | Authors |
0.40 | 23 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabian Prada | 1 | 23 | 2.00 |
| Misha Kazhdan | 2 | 4 | 0.74 |