Current state-of-the-art methods in variational image segmentation using level set methods are able to robustly segment complex textured images in an unsupervised manner. In recent...
Building on recent progress in modeling filter response statistics of natural images we integrate a statistical model into a variational framework for image segmentation. Incorpo...
In this paper, we introduce a novel approach for simultaneous restoration and segmentation of blurred, noisy images by approaching a variant of the Mumford-Shah functional from a ...
Abstract. We propose a variational framework for the integration multiple competing shape priors into level set based segmentation schemes. By optimizing an appropriate cost functi...
Daniel Cremers, Nir A. Sochen, Christoph Schnö...
In this paper, we present a variational Bayes (VB) approach for image segmentation. First, image is modeled by a mixture model, and then with the techniques of factor analyzer, th...
Zhenglong Li, Qingshan Liu, Jian Cheng, Hanqing Lu