Convex non-convex image segmentation

Raymond H. Chan, Alessandro Lanza, Serena Morigi, Fiorella Sgallari

Abstract: A convex non-convex variational model is proposed for multiphase image segmentation. We consider a specially designed non-convex regularization term which adapts spatially to the image structures for a better control of the segmentation boundary and an easy handling of the intensity inhomogeneities. The nonlinear optimization problem is efficiently solved by an alternating directions methods of multipliers procedure. We provide a convergence analysis and perform numerical experiments on several images, showing the effectiveness of this procedure.