Sparsity Constrained Estimation in Image Processing and Computer Vision
From MaRDI portal
Publication:4556987
DOI10.1007/978-3-319-61609-4_8zbMath1443.94029OpenAlexW2767010935MaRDI QIDQ4556987
Vishal Monga, Umamahesh Srinivas, Hojjat Seyed Mousavi
Publication date: 28 November 2018
Published in: Handbook of Convex Optimization Methods in Imaging Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-319-61609-4_8
Image analysis in multivariate analysis (62H35) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Computational aspects of data analysis and big data (68T09)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- The Adaptive Lasso and Its Oracle Properties
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- The variational Garrote
- A majorization-minimization approach to variable selection using spike and slab priors
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- The benefit of group sparsity
- Algorithms for simultaneous sparse approximation. II: Convex relaxation
- An algorithm for total variation minimization and applications
- Spike and slab variable selection: frequentist and Bayesian strategies
- On the adaptive elastic net with a diverging number of parameters
- The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
- A Majorize-Minimize Subspace Approach for $\ell_2-\ell_0$ Image Regularization
- Quasi-Cauchy Sequences
- NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
- Handbook of Face Recognition
- On Single Image Scale-Up Using Sparse-Representations
- Model selection and estimation in the Gaussian graphical model
- Image decomposition via the combination of sparse representations and a variational approach
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
- Bayesian Variable Selection in Linear Regression
- Dictionary Learning Algorithms for Sparse Representation
- Bayesian Compressive Sensing
- Sparse Reconstruction by Separable Approximation
- Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing
- A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed $\ell ^{0}$ Norm
- C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework
- Expectation-Maximization Gaussian-Mixture Approximate Message Passing
- Structured Sparse Priors for Image Classification
- Regression Shrinkage and Selection via The Lasso: A Retrospective
- Sparsity and Smoothness Via the Fused Lasso
- De-noising by soft-thresholding
- Average Case Analysis of Multichannel Sparse Recovery Using Convex Relaxation
- The Power of Convex Relaxation: Near-Optimal Matrix Completion
- Model-Based Compressive Sensing
- Regularization and Variable Selection Via the Elastic Net
- Sparse Bayesian Learning for Basis Selection
- Sparse solutions to linear inverse problems with multiple measurement vectors
- Hierarchical Bayesian Sparse Image Reconstruction With Application to MRFM
- Iterative Weighted Maximum Likelihood Denoising With Probabilistic Patch-Based Weights
- Bayesian Compressive Sensing Using Laplace Priors
- Fast Image Recovery Using Variable Splitting and Constrained Optimization
- Image Super-Resolution Via Sparse Representation
- Coupled Dictionary Training for Image Super-Resolution
- Learning with Structured Sparsity
- High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
- Model Selection and Estimation in Regression with Grouped Variables
- For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solution
- Stable signal recovery from incomplete and inaccurate measurements
