An efficient denoising framework using weighted overlapping group sparsity
From MaRDI portal
Publication:2195306
DOI10.1016/j.ins.2018.05.001zbMath1440.94014OpenAlexW2800744053MaRDI QIDQ2195306
M. N. S. Swamy, Ahlad Kumar, M. Omair Ahmad
Publication date: 8 September 2020
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2018.05.001
Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Related Items
Weighted hyper-Laplacian prior with overlapping group sparsity for image restoration under Cauchy noise ⋮ Multi-band weighted \(l_p\) norm minimization for image denoising ⋮ Low-rank with sparsity constraints for image denoising
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Nonlinear total variation based noise removal algorithms
- Image restoration using total variation with overlapping group sparsity
- Sparsity and persistence: mixed norms provide simple signal models with dependent coefficients
- Adaptive total variation image deblurring: a majorization-minimization approach
- Extensions of smoothing via taut strings
- Optimal approximations by piecewise smooth functions and associated variational problems
- Improved Total Variation-Type Regularization Using Higher Order Edge Detectors
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- High-Order Total Variation-Based Image Restoration
- A Signal Processing Approach to Generalized 1-D Total Variation
- Group-Sparse Signal Denoising: Non-Convex Regularization, Convex Optimization
- Recovery of Blocky Images from Noisy and Blurred Data
- Multiresolution Bilateral Filtering for Image Denoising
- No-Reference Image Quality Assessment in the Spatial Domain
