We address the problem of restoration of images obtained through a scattering medium. We present an efficient quasimaximum likelihood blind deconvolution approach based on the fas...
Michael M. Bronstein, Alexander M. Bronstein, Yeho...
A general framework for performing robust, unsupervised tissue classification in magnetic resonance images is presented. Tissue classification is formulated as an estimation probl...
Abstract - We propose a new method for image segmentation based on a variational regularization algorithm for image denoising. We modify the Rudin-Osher-Fatemi (ROF) model in [1] b...
—In this paper, we present a new model for deformations of shapes. A pseudolikelihood is based on the statistical distribution of the gradient vector field of the gray level. The...
The paper describes a new approach using a Conditional Random Fields (CRFs) to extract physical and logical layouts in unconstrained handwritten letters such as those sent by indi...