An alternating direction method for mixed Gaussian plus impulse noise removal
From MaRDI portal
Publication:2319190
DOI10.1155/2013/850360zbMath1470.94059OpenAlexW2064270814WikidataQ58917606 ScholiaQ58917606MaRDI QIDQ2319190
Ting-Zhu Huang, Si Wang, Xi-Le Zhao, Jun Liu
Publication date: 16 August 2019
Published in: Abstract and Applied Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2013/850360
Numerical optimization and variational techniques (65K10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)
Uses Software
Cites Work
- Unnamed Item
- Nonlinear total variation based noise removal algorithms
- A new method for removing mixed noises
- Two-phase approach for deblurring images corrupted by impulse plus Gaussian noise
- On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- A variable-penalty alternating directions method for convex optimization
- An algorithm for total variation minimization and applications
- A variational approach to remove outliers and impulse noise
- Restoration of images corrupted by mixed Gaussian-impulse noise via \(l_{1}-l_{0}\) minimization
- Iterative image restoration combining total variation minimization and a second-order functional
- Fourth-order partial differential equations for noise removal
- Alternating Direction Method with Gaussian Back Substitution for Separable Convex Programming
- A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
- A New Total Variation Method for Multiplicative Noise Removal
- The Split Bregman Method for L1-Regularized Problems
- Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time
- Minimizers of Cost-Functions Involving Nonsmooth Data-Fidelity Terms. Application to the Processing of Outliers
- Digital inpainting based on the Mumford–Shah–Euler image model
- Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization
- Framelet Algorithms for De-Blurring Images Corrupted by Impulse Plus Gaussian Noise
This page was built for publication: An alternating direction method for mixed Gaussian plus impulse noise removal