Fu et al., 2021 - Google Patents
Combining adaptive dictionary learning with nonlocal similarity for full-waveform inversionFu et al., 2021
View PDF- Document ID
- 1435186601929028369
- Author
- Fu H
- Qi H
- Hua R
- Publication year
- Publication venue
- Inverse Problems in Science and Engineering
External Links
Snippet
We study the full-waveform inversion (FWI) problem for the recovery of velocity model/image in acoustic media. FWI is formulated as a typical nonlinear optimization problem, many regularization techniques are used to guide the optimization process because the FWI …
- 230000003044 adaptive 0 title description 26
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20064—Wavelet transform [DWT]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2211/00—Image generation
- G06T2211/40—Computed tomography
- G06T2211/424—Iterative
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
- G06T11/006—Inverse problem, transformation from projection-space into object-space, e.g. transform methods, back-projection, algebraic methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/001—Image restoration
- G06T5/002—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Li et al. | NETT: solving inverse problems with deep neural networks | |
| Wu et al. | InversionNet: An efficient and accurate data-driven full waveform inversion | |
| Yu et al. | Monte Carlo data-driven tight frame for seismic data recovery | |
| Zhu et al. | Seismic data denoising through multiscale and sparsity-promoting dictionary learning | |
| Calvetti et al. | Hierachical Bayesian models and sparsity: ℓ2-magic | |
| Beckouche et al. | Simultaneous dictionary learning and denoising for seismic data | |
| Liang et al. | Seismic data restoration via data-driven tight frame | |
| Storath et al. | Joint image reconstruction and segmentation using the Potts model | |
| Belge et al. | Wavelet domain image restoration with adaptive edge-preserving regularization | |
| Zhou et al. | Adaptive tight frame based medical image reconstruction: a proof-of-concept study for computed tomography | |
| Zhang et al. | A fast adaptive reweighted residual-feedback iterative algorithm for fractional-order total variation regularized multiplicative noise removal of partly-textured images | |
| Jalobeanu et al. | Hyperparameter estimation for satellite image restoration using a MCMC maximum-likelihood method | |
| Buccini et al. | Modulus-based iterative methods for constrained ℓp–ℓq minimization | |
| Li et al. | Full waveform inversion with nonlocal similarity and model-derivative domain adaptive sparsity-promoting regularization | |
| Lu et al. | Gradient-based low rank method and its application in image inpainting | |
| Wang et al. | Data-driven multichannel seismic impedance inversion with anisotropic total variation regularization | |
| Liu et al. | Adaptive sparse coding on PCA dictionary for image denoising | |
| Starck et al. | Weak-lensing mass reconstruction using sparsity and a Gaussian random field | |
| Barbu | Nonlinear PDE model for image restoration using second-order hyperbolic equations | |
| Fu et al. | Reconstruction of seismic data with missing traces using normalized Gaussian weighted filter | |
| Gazzola et al. | An inner–outer iterative method for edge preservation in image restoration and reconstruction | |
| Obmann et al. | Deep synthesis network for regularizing inverse problems | |
| Fairag et al. | A two-level method for image denoising and image deblurring models using mean curvature regularization | |
| Lu et al. | An anisotropic alternating regularization-based reconstruction algorithm for cone beam computed laminography | |
| Zhao et al. | Noise reduction method based on curvelet theory of seismic data |