Estimation of a Fourier spectrum of the input data, followed by an inverse Fourier transform to output data onto a regular grid
Interpolating beyond spatial Nyquist is achieved by estimating the Fourier spectrum using matching pursuit. This is an iterative method where, for each iteration, a discrete Fourier transform of the data is first computed. Then, the Fourier component with maximum energy is selected.
This component is added to the estimated spectrum. Additionally, an inverse Fourier transform of the selected Fourier component is computed. Finally, the selected Fourier component from the input data is subtracted.
This approach makes use of ideas from compressive sensing theory, and provides reconstruction of data beyond what was thought possible according to classical sampling theory.
NExT offers a comprehensive training program to support users of the SLB software, plugins, and other software products.
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