TY - GEN
T1 - Constrained anisotropic diffusion and some applications
AU - Facciolo, Gabriele
AU - Lecumberry, Federico
AU - Almansa, Andrés
AU - Pardo, Alvaro
AU - Caselles, Vicent
AU - Rougé, Bernard
PY - 2006/1/1
Y1 - 2006/1/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/44749084349
M3 - Conference contribution
AN - SCOPUS:44749084349
SN - 1904410146
SN - 9781904410140
T3 - BMVC 2006 - Proceedings of the British Machine Vision Conference 2006
SP - 1049
EP - 1058
BT - BMVC 2006 - Proceedings of the British Machine Vision Conference 2006
PB - British Machine Vision Association, BMVA
T2 - 2006 17th British Machine Vision Conference, BMVC 2006
Y2 - 4 September 2006 through 7 September 2006
ER -