Name
Abstract | ||
|---|---|---|
In this paper, we introduce a new diffusion algorithm that can be used for reducing aliasing on both step edges and lines. It derives from the diffusion model of Perona and Malik, and works as an adaptive level-curve method in which diffusion is carried out in the normal direction of the gradient for step edges, while the eigenvalues of the Hessian matrix are used for lines. To get sharp images, we use high-pass filters to preserve as much as possible the high frequency content while diffusing. Experimental tests using grayscale and colour images show that our algorithm efficiently reduces aliasing. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.patcog.2011.08.023 | Pattern Recognition |
Keywords | Field | DocType |
normal direction,high frequency content,experimental test,hessian matrix,adaptive level-curve method,new diffusion algorithm,diffusion model,step edge,pde-based diffusion,high-pass filter,colour image,lines,aliasing,curvature,diffusion | Anisotropic diffusion,Hessian matrix,Artificial intelligence,Geometry,Grayscale,Eigenvalues and eigenvectors,Curvature,Pattern recognition,Algorithm,Aliasing,Mathematics,Diffusion (business),Normal | Journal |
Volume | Issue | ISSN |
45 | 3 | 0031-3203 |
Citations | PageRank | References |
0 | 0.34 | 20 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Djemel Ziou | 1 | 1395 | 99.40 |
| Alain Horé | 2 | 169 | 9.54 |