A variational model for multiplicative structured noise removal
type: Item
instance of: scholarly article
title: A variational model for multiplicative structured noise removal
zbMATH Open document ID: 1380.94019
author: Paul Escande
author: Pierre Weiss
author: Wenxing Zhang
published in: Journal of Mathematical Imaging and Vision
publication date: 2018-02-08T00:00:00Z
Mathematics Subject Classification ID: 94A08
Mathematics Subject Classification ID: 65K10
Mathematics Subject Classification ID: 68U10
Mathematics Subject Classification ID: 49M29
Mathematics Subject Classification ID: 92C55
zbMATH DE Number: 6836254
zbMATH Keywords: denoising
zbMATH Keywords: multiplicative noise
zbMATH Keywords: stationary noise
zbMATH Keywords: variational method
zbMATH Keywords: convex optimization
describes a project that uses: Fiji
MaRDI profile type: Publication
full work available at URL: s10851-016-0667-3
OpenAlex ID: W2429289397
cites work: A Variational Approach to Removing Multiplicative Noise
cites work: An algorithm for total variation minimization and applications
cites work: A first-order primal-dual algorithm for convex problems with applications to imaging
cites work: Iterative Weighted Maximum Likelihood Denoising With Probabilistic Patch-Based Weights
cites work: A convex variational model for restoring blurred images with multiplicative noise
cites work: Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients
cites work: Processing stationary noise: model and parameter selection in variational methods
cites work: Variational Algorithms to Remove Stationary Noise: Applications to Microscopy Imaging
cites work: Multiplicative Noise Removal via a Learned Dictionary
cites work: The distribution of the sum of independent gamma random variables
cites work: Convex Analysis
cites work: A Nonlinear Inverse Scale Space Method for a Convex Multiplicative Noise Model
cites work: Removing multiplicative noise by Douglas-Rachford splitting methods
cites work: A new convex optimization model for multiplicative noise and blur removal
DOI: 10.1007/S10851-016-0667-3
description: scientific article; zbMATH DE number 6836254