Multi-dimensional data reconstruction constrained by a regularly interpolated model
US9158016B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 1, 2012 |
| Grant date | Oct 13, 2015 |
| Priority date | — |
| Expiry date | Aug 28, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01V2210/57
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A process for overcoming aliasing using a minimum weighted norm interpolation (MWNI) technique may include computing an initial, regularly interpolated model with no data gaps and computing a plurality of initial spectral weights using the initial, regularly interpolated model. The initial, regularly interpolated model is used to compute the spectral weights as initial constraints in a least-squares solution methodology. The initial spectral weights are used as initial constraints in a constrained minimum weighted norm interpolation data reconstruction. The process may further include converting the initial, regularly interpolated model into a frequency domain and computing unknown spectral weights from frequency data at each frequency slice of the initial, regularly interpolated model using Fourier transform. The process results in reducing aliasing artifacts and improving data regularization.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.