Image denoising based on improved data-driven sparse representation
Explore this paper's citation graph
Summary
Numerical results on denoising experiments demonstrate that the proposed algorithm overall outperforms the original data-driven tight frame construction scheme on both the recovery quality and computational time.
- Type
- preprint
- Published
- 2015-02-11
- Cited by
- 1
- References
- 30
- Access
- Open access
- OpenAlex
- https://openalex.org/W1657810653
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:10691035
Keywords
Sparse approximation, Noise reduction, Frame (networking), Representation (politics), Computer science
References
- Sparse and Redundant Representations - From Theory to Applications in Signal and Image Processing
- A Low Patch-Rank Interpretation of Texture
- Nonlocally Centralized Sparse Representation for Image Restoration
- Linearized Bregman Iterations for Frame-Based Image Deblurring
- A framelet-based image inpainting algorithm
- Data-driven tight frame construction and image denoising
- Nonlocal Image Restoration With Bilateral Variance Estimation: A Low-Rank Approach
- The [barred L]ojasiewicz Inequality for Nonsmooth Subanalytic Functions with Applications to Subgradient Dynamical Systems
- Image restoration: Total variation, wavelet frames, and beyond
- Proximal alternating linearized minimization for nonconvex and nonsmooth problems
- Sparsity-based image denoising via dictionary learning and structural clustering
- Framelet-Based Blind Motion Deblurring From a Single Image
- Multiplicative Noise Removal via a Learned Dictionary
- Regularized Generalized Inverse Accelerating Linearized Alternating Minimization Algorithm for Frame-Based Poissonian Image Deblurring
- Weighted Nuclear Norm Minimization with Application to Image Denoising
- Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
- Learning Multiscale Sparse Representations for Image and Video Restoration
- Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients
- Multiplicative Denoising Based on Linearized Alternating Direction Method Using Discrepancy Function Constraint
- Two-stage image denoising by principal component analysis with local pixel grouping
Cited by
Related papers
- Simulation on the Seeker Signal Wavelets Denoising Based on Parameters Optimization
- An ICI Based Algorithm for Fast Denoising of Video Signals
- Multiple forward-backward strategies for two-stage video denoising
- A New Method for Sparse Signal Denoising Based on Compressed Sensing
- Video denoising via online sparse and low-rank matrix decomposition
- Video Denoising Using Spatio-temporal Filtering
- VIDEO DENOISING AND QUALITY IMPROVEMENT USING NEW THRESHOLDING BASED DWT & DAMMW ALGORITHM
- Overview on sparse image denoising