An improved variational model for denoising magnetic resonance images

DOI10.1016/j.camwa.2018.05.044zbMath1442.92086OpenAlexW2889219388MaRDI QIDQ2202992

Jian-Jun Yuan

Publication date: 1 October 2020

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2018.05.044

zbMATH Keywords

variational modelADMM algorithmRician noiseMRI denoisinggradient fidelity

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items

Image denoising via a new hybrid TGV model based on Shannon interpolation, Magnetic resonance images denoising using a wavelet solution to Laplace equation associated with a new variational model, Efficient Boosted DC Algorithm for Nonconvex Image Restoration with Rician Noise, Variational Rician Noise Removal via Splitting on Spheres

Uses Software

• FSIM
• DnCNN

Cites Work

• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Speckle reduction with trained nonlinear diffusion filtering
• A convex variational model for restoring blurred images with large Rician noise
• A Variational Approach to Removing Multiplicative Noise
• Sparse Reconstruction by Separable Approximation
• Mixed Noise Removal via Laplacian Scale Mixture Modeling and Nonlocal Low-Rank Approximation
• Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization
• FSIM: A Feature Similarity Index for Image Quality Assessment
• A Review of Image Denoising Algorithms, with a New One