Boosting of Image Denoising Algorithms
DOI10.1137/140990978zbMath1341.94006arXiv1502.06220OpenAlexW1829781029MaRDI QIDQ3192649
Publication date: 13 October 2015
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1502.06220
regularizationgraph theorydenoisingimage restorationboostingsparse representationgraph LaplacianK-SDV
Image analysis in multivariate analysis (62H35) Graphs and linear algebra (matrices, eigenvalues, etc.) (05C50) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Linear operators and ill-posed problems, regularization (47A52)
Related Items (12)
Cites Work
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Nonlinear total variation based noise removal algorithms
- Local and nonlocal discrete regularization on weighted graphs for image and mesh processing
- Nonlocal discrete \(p\)-Laplacian driven image and manifold processing
- Non-negative matrices and Markov chains. 2nd ed
- Perturbation of the eigenvectors of the graph Laplacian: application to image denoising
- A fast algorithm for matrix balancing
- Secrets of image denoising cuisine
- Nonlocal Operators with Applications to Image Processing
- Nonlocal Linear Image Regularization and Supervised Segmentation
- Sparse and Redundant Representations
- From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
- Atomic Decomposition by Basis Pursuit
- Boosting With theL2Loss
- $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
- Global Image Denoising
- Progressive Image Denoising Through Hybrid Graph Laplacian Regularization: A Unified Framework
- Single Image Interpolation Via Adaptive Nonlocal Sparsity-Based Modeling
- A General Framework for Regularized, Similarity-Based Image Restoration
- Symmetric Smoothing Filters From Global Consistency Constraints
- Local Smoothing Neighborhood Filters
- Generalizing the Nonlocal-Means to Super-Resolution Reconstruction
- Patch-Based Near-Optimal Image Denoising
- Solving Inverse Problems With Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity
- How to SAIF-ly Boost Denoising Performance
- Image Processing Using Smooth Ordering of its Patches
- An Iterative Regularization Method for Total Variation-Based Image Restoration
- A Review of Image Denoising Algorithms, with a New One
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