Gaussian Patch Mixture Model Guided Low-Rank Covariance Matrix Minimization for Image Denoising

DOI10.1137/21M1454262OpenAlexW4302307396MaRDI QIDQ5056914

No author found.

Publication date: 8 December 2022

Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/21m1454262

zbMATH Keywords

covariance matriximage denoisingGaussian mixture modelnuclear normlow-rank matrix factorization

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• BSDS
• BM3D

Cites Work

• Unnamed Item
• Unnamed Item
• Nonlinear total variation based noise removal algorithms
• Optimal rates of convergence for sparse covariance matrix estimation
• Fields of experts
• A trace inequality of John von Neumann
• Convergence theorems for the non-local means filter
• Kernel Wiener filtering model with low-rank approximation for image denoising
• Data-driven tight frame construction and image denoising
• Optimal estimation and rank detection for sparse spiked covariance matrices
• Low rank prior and total variation regularization for image deblurring
• Sparse and low-rank covariance matrix estimation
• On the principal components of sample covariance matrices
• Total Generalized Variation in Diffusion Tensor Imaging
• A Nonlocal Bayesian Image Denoising Algorithm
• Robust principal component analysis?
• A Singular Value Thresholding Algorithm for Matrix Completion
• The Split Bregman Method for L1-Regularized Problems
• Structure-Based Low-Rank Model With Graph Nuclear Norm Regularization for Noise Removal
• Nonlocal Means and Optimal Weights for Noise Removal
• De-noising by soft-thresholding
• Positive-Definite ℓ₁-Penalized Estimation of Large Covariance Matrices
• From Rank Estimation to Rank Approximation: Rank Residual Constraint for Image Restoration
• Image Restoration via Simultaneous Nonlocal Self-Similarity Priors
• Group Sparsity Residual Constraint With Non-Local Priors for Image Restoration
• Invariant $\varphi$-Minimal Sets and Total Variation Denoising on Graphs
• Covariance Matrix Estimation for the Cryo-EM Heterogeneity Problem
• Generalized Thresholding of Large Covariance Matrices
• A Nonlocal Denoising Algorithm for Manifold-Valued Images Using Second Order Statistics
• An Efficient Two-Phase ${\rm L}^{1}$-TV Method for Restoring Blurred Images with Impulse Noise
• Nonlocal Image Restoration With Bilateral Variance Estimation: A Low-Rank Approach
• Nonlocally Centralized Sparse Representation for Image Restoration
• A Review of Image Denoising Algorithms, with a New One
• A Corrected Tensor Nuclear Norm Minimization Method for Noisy Low-Rank Tensor Completion

This page was built for publication: Gaussian Patch Mixture Model Guided Low-Rank Covariance Matrix Minimization for Image Denoising