Tomographic inversion using -norm regularization of wavelet coefficients
arXiv:physics/0608094 · doi:10.1111/j.1365-246X.2007.03409.x
Abstract
We propose the use of regularization in a wavelet basis for the solution of linearized seismic tomography problems , allowing for the possibility of sharp discontinuities superimposed on a smoothly varying background. An iterative method is used to find a sparse solution that contains no more fine-scale structure than is necessary to fit the data to within its assigned errors.
19 pages, 14 figures. Submitted to GJI July 2006. This preprint does not use GJI style files (which gives wrong received/accepted dates). Corrected typo
Cited by in corpus (18)
- Accelerated Projected Gradient Method for Linear Inverse Problems with Sparsity Constraints
- Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography
- Accelerating gradient projection methods for -constrained signal recovery by steplength selection rules
- On the performance of algorithms for the minimization of -penalized functionals
- Nonlinear regularization techniques for seismic tomography
- Discretization-invariant Bayesian inversion and Besov space priors
- Sparsity-promoting and edge-preserving maximum a posteriori estimators in non-parametric Bayesian inverse problems
- TorchRadon: Fast Differentiable Routines for Computed Tomography
- Full waveform inversion with nonlocal similarity and model-derivative domain adaptive sparsity-promoting regularization
- Wavelets and wavelet-like transforms on the sphere and their application to geophysical data inversion
- Iterative algorithms for total variation-like reconstructions in seismic tomography
- L1Packv2: A Mathematica package for minimizing an -penalized functional
- Sparse dynamic tomography. A shearlet-based approach for iodine perfusion in plant stems
- Posterior sampling for inverse imaging problems on the sphere in seismology and cosmology
- Improved full-waveform inversion for seismic data in the presence of noise based on the K-support norm
- Shearlet-based regularization in statistical inverse learning with an application to X-ray tomography
- Regularization with optimal space-time priors
- Eigenvector Model Descriptors for Solving an Inverse Problem of Helmholtz Equation: Extended Materials