A variational representation for efficient noisy segmentation

Abstract

In this paper we focus on a novel technique VRENS, (Variational Representation for Efficient Noisy Segmentation) to segment images (i.e. containg also textures) under noise. It is based on a hierarchical representation obtained by a combination of the classical weak membrane and a simpler region competition method. VRENS seems to be an interesting algorithm because of its robustness to added gaussian noise along with a low computational cost.