Image restoration via simultaneous sparse coding: where structured sparsity meets Gaussian scale mixture
From MaRDI portal
Publication:1799981
DOI10.1007/s11263-015-0808-yzbMath1398.94029OpenAlexW2111557737MaRDI QIDQ1799981
Weisheng Dong, Yi Ma, Xin Li, GuangMing Shi
Publication date: 19 October 2018
Published in: International Journal of Computer Vision (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11263-015-0808-y
Gaussian scale mixturesimultaneous sparse codingstructured sparsityvariational image restorationalternative minimization
Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Related Items (7)
Image Denoising: The Deep Learning Revolution and Beyond—A Survey Paper ⋮ Adaptive spatial-spectral dictionary learning for hyperspectral image restoration ⋮ Low-rank with sparsity constraints for image denoising ⋮ Iterative adaptive nonconvex low-rank tensor approximation to image restoration based on ADMM ⋮ The Little Engine that Could: Regularization by Denoising (RED) ⋮ Solving inverse problems using data-driven models ⋮ Regularization by Denoising via Fixed-Point Projection (RED-PRO)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Image super-resolution by TV-regularization and Bregman iteration
- From local kernel to nonlocal multiple-model image denoising
- Cardinal spline filters: Stability and convergence to the ideal sinc interpolator
- Adaptive wavelet thresholding for image denoising and compression
- Image denoising using scale mixtures of gaussians in the wavelet domain
- Learning Multiscale Sparse Representations for Image and Video Restoration
- Orthonormal bases of compactly supported wavelets
- A Biometrics Invited Paper. The Analysis and Selection of Variables in Linear Regression
- Multiresolution Approximations and Wavelet Orthonormal Bases of L 2 (R)
- Ideal spatial adaptation by wavelet shrinkage
- 10.1162/15324430152748236
- An Empirical Bayesian Strategy for Solving the Simultaneous Sparse Approximation Problem
- Bayesian Compressive Sensing
- Recovering Sparse Signals With a Certain Family of Nonconvex Penalties and DC Programming
- $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
- Embedded image coding using zerotrees of wavelet coefficients
- Latent Variable Bayesian Models for Promoting Sparsity
- Sparse Bayesian Learning for Basis Selection
- Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems
- Image Super-Resolution Via Sparse Representation
- BM3D Frames and Variational Image Deblurring
- Solving Inverse Problems With Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity
- Universal Regularizers for Robust Sparse Coding and Modeling
- Nonlocal Image Restoration With Bilateral Variance Estimation: A Low-Rank Approach
- Nonlocally Centralized Sparse Representation for Image Restoration
- A Simplex Method for Function Minimization
- A Review of Image Denoising Algorithms, with a New One
This page was built for publication: Image restoration via simultaneous sparse coding: where structured sparsity meets Gaussian scale mixture