Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging
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Publication:3454501
DOI10.1137/141002293zbMath1343.94013arXiv1501.02923OpenAlexW2189938900MaRDI QIDQ3454501
Saiprasad Ravishankar, Yoram Bresler
Publication date: 25 November 2015
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1501.02923
inverse problemsmedical imagingmagnetic resonance imagingsparse representationcompressed sensingdictionary learningsparsifying transforms
Computational methods for sparse matrices (65F50) Learning and adaptive systems in artificial intelligence (68T05) Biomedical imaging and signal processing (92C55) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
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Cites Work
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- Solving quadratically constrained least squares problems using a differential-geometric approach
- A block coordinate variable metric forward-backward algorithm
- Structured overcomplete sparsifying transform learning with convergence guarantees and applications
- A self-referencing level-set method for image reconstruction from sparse Fourier samples
- Least angle regression. (With discussion)
- A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion
- Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality
- Sparse and Redundant Modeling of Image Content Using an Image-Signature-Dictionary
- Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Decoding by Linear Programming
- Stable recovery of sparse overcomplete representations in the presence of noise
- From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
- Learning Multiscale Sparse Representations for Image and Video Restoration
- Atomic Decomposition by Basis Pursuit
- Variational Analysis
- Dictionary Learning for Sparse Approximations With the Majorization Method
- Recursive Least Squares Dictionary Learning Algorithm
- Learning Sparsifying Transforms
- Sparsifying Transform Learning With Efficient Optimal Updates and Convergence Guarantees
- $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
- Learning Filter Bank Sparsifying Transforms
- Sparse Approximate Solutions to Linear Systems
- Matching pursuits with time-frequency dictionaries
- Subspace Pursuit for Compressive Sensing Signal Reconstruction
- Blind Compressed Sensing
- Dictionary Identification—Sparse Matrix-Factorization via $\ell_1$-Minimization
- Analysis versus synthesis in signal priors
- Wavelet-Based Compressed Sensing Using a Gaussian Scale Mixture Model
- Learning Doubly Sparse Transforms for Images
- For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solution
- Compressed sensing
- Convergence of a block coordinate descent method for nondifferentiable minimization
- Adaptive greedy approximations
