The search for efficient image denoising methods is still a valid challenge at the crossing of
functional analysis and statistics. In spite of the sophistication of the recently proposed …

Since their introduction in a classic paper by Rudin, Osher and Fatemi [26], total variation
minimizing models have become one of the most popular and successful methodology for …

We introduce a new iterative regularization procedure for inverse problems based on the
use of Bregman distances, with particular focus on problems arising in image processing …

A critical issue in image restoration is the problem of noise removal while keeping the
integrity of relevant image information. Denoising is a crucial step to increase image quality …

Imaging is an interdisciplinary research area with profound applications in many areas of
science, engineering, technology, and medicine. The most primitive form of imaging is visual …

Neighborhood filters are nonlocal image and movie filters which reduce the noise by
averaging similar pixels. The first object of the paper is to present a unified theory of these …

This paper focuses on the problem of multiplicative noise removal. We draw our inspiration
from the modeling of speckle noise. By using a MAP estimator, we can derive a functional …

The total variation--based image denoising model of Rudin, Osher, and Fatemi [Phys. D,
60,(1992), pp. 259--268] has been generalized and modified in many ways in the literature; …

This paper explores various aspects of the image decomposition problem using modern
variational techniques. We aim at splitting an original image f into two components u and ρ …

We are motivated by a recently developed nonlinear inverse scale space method for image
denoising [M. Burger, G. Gilboa, S. Osher, and J. Xu, Commun. Math. Sci., 4 (2006), pp. 179 …