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Nonlinear eigenfunctions, induced by subgradients of one-homogeneous functionals (such as the 1-Laplacian), have shown to be instrumental in segmentation, clustering and image decomposition. We present a class of flows for finding such eigenfunctions, generalizing a method recently suggested by Nossek-Gilboa. We analyze the flows on grids and graphs in the time-continuous and time-discrete settings. Several examples are provided showing how such flows can be used on images and graphs.
This presentation is part of Minisymposium “MS39 - Nonlinear Spectral Theory and Applications (part 2)”
organized by: Aujol Jean-Francois (University of Bordeaux) , Gilboa Guy (Electrical Engineering Department, Technion) .