Scale Selection for Compact Scale-Space Representation of Vector-Valued Images.

Iris Vanhamel, Cosmin Mihai, Hichem Sahli, Antonis Katartzis, Ioannis Pratikakis

Abstract: This paper investigates the scale selection problem for nonlinear diffusion scale-spaces. This topic comprises the notions of localization scale selection and scale space discretization. For the former, we present a new approach. It aims at maximizing the image content’s presence by finding the scale that has a maximum correlation with the noise-free image. For the latter, we propose to adapt the optimal diffusion stopping time criterion of Mrázek and Navara in such a way that it may identify multiple scales of importance.