A Sampling Theorem for Deconvolution in Two Dimensions
DOI10.1137/20M1329615zbMath1458.94053arXiv2003.13784OpenAlexW3094624080MaRDI QIDQ5143314
Joseph McDonald, Carlos Fernandez-Granda, Brett Bernstein
Publication date: 11 January 2021
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2003.13784
convex optimizationsampling theorydeconvolutionsparsitysuper-resolutiondual certificateGaussian convolution
Convex programming (90C25) Optimality conditions and duality in mathematical programming (90C46) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Duality theory (optimization) (49N15) Sampling theory in information and communication theory (94A20)
Uses Software
Cites Work
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- Robust recovery of stream of pulses using convex optimization
- Exact reconstruction using Beurling minimal extrapolation
- Super-resolution from noisy data
- Exact support recovery for sparse spikes deconvolution
- Exact matrix completion via convex optimization
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Decoding by Linear Programming
- Compressive Sensing by Random Convolution
- Linear Inversion of Band-Limited Reflection Seismograms
- Sampling Moments and Reconstructing Signals of Finite Rate of Innovation: Shannon Meets Strang–Fix
- Sampling Schemes for Multidimensional Signals With Finite Rate of Innovation
- Super-resolution of point sources via convex programming
- Towards Generalized FRI Sampling With an Application to Source Resolution in Radioastronomy
- Stable Support Recovery of Stream of Pulses With Application to Ultrasound Imaging
- MultiDimensional Sparse Super-Resolution
- Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems
- Superresolution without separation
- Demixing sines and spikes: Robust spectral super-resolution in the presence of outliers
- Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation
- Compressed Sensing Off the Grid
- Sampling signals with finite rate of innovation
- Exact Sampling Results for Some Classes of Parametric Nonbandlimited 2-D Signals
- Deconvolution of Point Sources: A Sampling Theorem and Robustness Guarantees
- Towards a Mathematical Theory of Super‐resolution
- Phase Retrieval via Matrix Completion
- Compressed sensing
