Resumen
Minimal surface regularization has been used in several applications ranging from stereo to image segmentation, sometimes hidden as a graph-cut discrete formulation, or as a strictly convex approximation to TV minimization. In this paper we consider a modified version of minimal surface regularization coupled with a robust data fitting term for interpolation purposes, where the corresponding evolution equation is constrained to diffuse only along the isophotes of a given image u and we design a convergent numerical scheme to accomplish this. To illustrate the usefulness of our approach, we apply this framework to the digital elevation model interpolation and to constrained vector probability diffusion.
| Idioma original | Inglés |
|---|---|
| Páginas | 1049-1058 |
| Número de páginas | 10 |
| Estado | Publicada - 2006 |
| Evento | 2006 17th British Machine Vision Conference, BMVC 2006 - Edinburgh Duración: 4 set. 2006 → 7 set. 2006 |
Conferencia
| Conferencia | 2006 17th British Machine Vision Conference, BMVC 2006 |
|---|---|
| País/Territorio | United Kingdom |
| Ciudad | Edinburgh |
| Período | 4/09/06 → 7/09/06 |