Rank minimization with applications to image noise removal
From MaRDI portal
Publication:781854
DOI10.1016/j.ins.2017.10.047zbMath1436.94008OpenAlexW2766804299MaRDI QIDQ781854
Hui-Yin Yan, Xue Yang, You-Wei Wen, Yu-Mei Huang
Publication date: 20 July 2020
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2017.10.047
block matchingnuclear normgamma multiplicative noise removalnonlocal self-similarityrank minimization problemwhite Gaussian additive noise removal
Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Matrix completion problems (15A83)
Related Items
Multi-band weighted \(l_p\) norm minimization for image denoising, Selecting Regularization Parameters for Nuclear Norm--Type Minimization Problems, A class of modified modulus-based synchronous multisplitting iteration methods for linear complementarity problems, HTR-CTO algorithm for wireless data recovery, Kernel Wiener filtering model with low-rank approximation for image denoising, Patch-based weighted SCAD prior for compressive sensing, Multiplicative Noise Removal: Nonlocal Low-Rank Model and Its Proximal Alternating Reweighted Minimization Algorithm, Tensor \(N\)-tubal rank and its convex relaxation for low-rank tensor recovery, Tensor train rank minimization with nonlocal self-similarity for tensor completion, Two-stage image denoising via an enhanced low-rank prior
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Solving semidefinite-quadratic-linear programs using SDPT3
- Nonlinear total variation based noise removal algorithms
- Fixed point and Bregman iterative methods for matrix rank minimization
- Stein block thresholding for image denoising
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- The computational complexity of some problems of linear algebra
- An algorithm for total variation minimization and applications
- Exact matrix completion via convex optimization
- On cone-invariant linear matrix inequalities
- A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise
- A Singular Value Thresholding Algorithm for Matrix Completion
- A Variational Approach to Removing Multiplicative Noise
- On the rank minimization problem over a positive semidefinite linear matrix inequality
- Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones
- Compressive Sensing via Nonlocal Low-Rank Regularization
- Robust Image Restoration via Adaptive Low-Rank Approximation and Joint Kernel Regression
- Weighted Schatten <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math> </inline-formula>-Norm Minimization for Image Denoising and Background Subtraction
- Structure-Based Low-Rank Model With Graph Nuclear Norm Regularization for Noise Removal
- The Power of Convex Relaxation: Near-Optimal Matrix Completion
- Multiplicative Noise Removal via a Learned Dictionary
- Nonlocal Image Restoration With Bilateral Variance Estimation: A Low-Rank Approach
- New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise
- An Iterative Regularization Method for Total Variation-Based Image Restoration
- A Review of Image Denoising Algorithms, with a New One
- Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients