Image Processing Reference
In-Depth Information
(Choice 6) using a permittivity of 1.2 and a minimum of 12 sources
and 120 receivers. For the prior use 3 separate prior shapes to match
the target configuration (some experimentation may be required). How
does the reconstructed image using the PDFT method compare with
the Born reconstruction? Once the prior was properly configured did
it improve the performance of the reconstructed images?
Advanced exercises
1. Use Cepstrum2 in MATLAB to generate Born and Cepstrum recon-
structions for any target consisting of two objects (Choice 1, 3, or 5)
using a permittivity of 1.5 and a minimum of 12 sources and 120 receiv-
ers. Please discuss your observations for each Born and Cepstrum
reconstruction paying special attention to the scales. Which method
performs the best? Why do you think this is?
2. Choose any target and any valid permittivity available in Cepstrum .
Using your choice, calculate the 2-D value for N , the minimum degrees
of freedom number described in Chapter 6. Now using your scenario
choice and the associated calculated value of N , generate reconstruc-
tions using Cepstrum such that the combined choice for number of
sources and receivers satisfies the conditions for N , N 2 /2, N 2 , 2 N 2 ,
4 N 2 , 8 N 2 , and 16 N 2 . Do not forget to add jitter bandwidth as needed to
overcome aliasing. For which scenario does the reconstructed image
begin to look useful? What happens to the image as you increase the
source/receiver numbers above this threshold?
3. Repeat Exercise 2 above except this time use pdFt in lieu of Cep-
strum2. Utilize the PDFT method in your reconstructions and see if
this has any effect on the performance of the reconstructions. Does
this change the minimum threshold for degrees of freedom?
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