Multifrequency beam-based migration in inhomogeneous media using windowed Fourier transform frames

2020 ◽  
Vol 223 (2) ◽  
pp. 1086-1099
Author(s):  
Ram Tuvi ◽  
Zeyu Zhao ◽  
Mrinal K Sen

SUMMARY We consider the problem of inhomogeneous subsurface imaging using beam waves. The formulation is based on the ultra-wide-band phase-space beam summation (UWB-PS-BS) method, which is structured upon windowed Fourier transform (WFT) expansions of surface fields and sources. In this approach, the radiated field is given as a superposition of beam propagators. Here, we use the beams first for expanding the surface sources and the scattered data, and then for imaging where we use the backpropagation and cross-correlation of beams. This formulation enables a target oriented imaging approach, where we take into account only pairs of source and receiver beams that pass near a region of interest, and thus extract only the relevant data arriving from this region. It also leads to a priori sparse representation of both the beam domain data and the beam propagators. A physical cogent for the beam domain data is obtained under the Born approximation. The beam domain data can be approximated as the local interaction between the beam propagators and the medium reflectivity. Thus, one may interpret the beam domain data as a local Snell’s law reflection in the direction defined by the vector summation of the incident beam and backpropagated beam ray parameters. We demonstrate a physical model for the beam domain data and the salient features of the proposed imaging algorithm using numerical examples.

2020 ◽  
Vol 31 (7) ◽  
pp. 074007 ◽  
Author(s):  
John J Charonko ◽  
Dominique Fratantonio ◽  
J Michael Mayer ◽  
Ankur Bordoloi ◽  
Kathy P Prestridge

Author(s):  
D. E. Luzzi ◽  
L. D. Marks ◽  
M. I. Buckett

As the HREM becomes increasingly used for the study of dynamic localized phenomena, the development of techniques to recover the desired information from a real image is important. Often, the important features are not strongly scattering in comparison to the matrix material in addition to being masked by statistical and amorphous noise. The desired information will usually involve the accurate knowledge of the position and intensity of the contrast. In order to decipher the desired information from a complex image, cross-correlation (xcf) techniques can be utilized. Unlike other image processing methods which rely on data massaging (e.g. high/low pass filtering or Fourier filtering), the cross-correlation method is a rigorous data reduction technique with no a priori assumptions.We have examined basic cross-correlation procedures using images of discrete gaussian peaks and have developed an iterative procedure to greatly enhance the capabilities of these techniques when the contrast from the peaks overlap.


2000 ◽  
Vol 54 (3) ◽  
pp. 396-401,018 ◽  
Author(s):  
Hitomi Miyata ◽  
Makoto Shinozaki

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