Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
We study geometric reconstruction problems in one-dimensional retina vision. In such problems, the scene is modeled as a 2D plane, and the camera sensor produces 1D images of the s...
Olof Enqvist, Fredrik Kahl, Carl Olsson, Kalle &Ar...
We generalize the primal-dual hybrid gradient (PDHG) algorithm proposed by Zhu and Chan in [M. Zhu, and T. F. Chan, An Efficient Primal-Dual Hybrid Gradient Algorithm for Total Var...
The goal of this note is to generalize the topological gradient method, applied to restoration and classification problems for grey-level images, to color images. We illustrate ou...
We propose two algorithms based on Bregman iteration and operator splitting technique for nonlocal TV regularization problems. The convergence of the algorithms is analyzed and ap...
Xiaoqun Zhang, Martin Burger, Xavier Bresson, Stan...
We consider the inverse problem of reconstructing thin tubular inclusions inside some three-dimensional body from measurements of electrostatic currents and potentials on its bound...
In image processing, the Rudin-Osher-Fatemi (ROF) model [L. Rudin, S. Osher, and E. Fatemi, Physica D, 60(1992), pp. 259–268] based on total variation (TV) minimization has prove...
Surface registration, which transforms different sets of surface data into one common reference space, is an important process which allows us to compare or integrate the surface ...
Lok Ming Lui, Sheshadri R. Thiruvenkadam, Yalin Wa...
We present a novel deconvolution approach to accurately restore piecewise smooth signals from blurred data. The first stage uses Higher Order Total Variation restorations to obtai...