We describe how implicit surface representations can be used to solve fundamental
problems in brain imaging. This kind of representation is not only natural following the state …

We are interested in PDE's (Partial Differential Equations) in order to smooth multi-valued
images in an anisotropic manner. Starting from a review of existing anisotropic …

Spectral methods have recently gained popularity in many domains of computer graphics
and geometry processing, especially shape processing, computation of shape descriptors …

Most denoising and enhancement methods for color images have been formulated on linear
color models, namely, the channel-by-channel model and vectorial model. In this paper, we …

We introduce a new nonsmooth variational model for the restoration of manifold-valued data
which includes second order differences in the regularization term. While such models were …

Nonlinear diffusion equations are now widely used to restore and enhance images. They
allow to eliminate noise and artifacts while preserving large global features, such as object …

In this article, we propose a local and geometric point of view of vector image filtering using
diffusion PDEs. It allows us to analyze proposed methods of vector data regularization, as …

This manuscript is devoted to variational models, their corresponding Euler–Lagrange
equations and numerical implementations for image processing. Such techniques allow us …

We consider total variation (TV) minimization for manifold-valued data. We propose a cyclic
proximal point algorithm and a parallel proximal point algorithm to minimize TV functionals …

Publisher Summary Multichannel image regularization is a fundamental process in many
image processing and computer vision algorithms. It is necessary to gain full control of this …