Publications associées à Inverse problems in acoustic tomography

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Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

Inverse problems in acoustic tomography

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Graph Based Sinogram Denoising for Tomographic Reconstructions

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Optical Tomographic Image Reconstruction Based on Beam Propagation and Sparse Regularization

MR Image Reconstruction from Generalized Projections

Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

Compressed Sensing of Memoryless Sources

Multiscale Interior Tomography Using 1D Generalized Total Variation

Eigensensing And Deconvolution For The Reconstruction Of Heat Absorption Profiles From Photoacoustic Tomography Data

Recursive Compressed Sensing

Compressed Optical Imaging

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Compressed Sensing of Memoryless Sources

Compressed Optical Imaging

Graph Based Sinogram Denoising for Tomographic Reconstructions

Eigensensing And Deconvolution For The Reconstruction Of Heat Absorption Profiles From Photoacoustic Tomography Data

Recursive Compressed Sensing

Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

Optical Tomographic Image Reconstruction Based on Beam Propagation and Sparse Regularization

MR Image Reconstruction from Generalized Projections

Multiscale Interior Tomography Using 1D Generalized Total Variation