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Material Type: Notes; Class: Digital Image Processing; Subject: Electrical & Computer Engr; University: Georgia Institute of Technology-Main Campus; Term: Fall 2003;
Typology: Study notes
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ECE 6258 Russell M. Mersereau
ECE 6258 Russell M. Mersereau
ECE 6258 Russell M. Mersereau
) ˆ
( 1
u
p
) ˆ
( 2
u
p
) ˆ
( 3
u
p
ECE 6258 Russell M. Mersereau
0
ECE 6258 Russell M. Mersereau
Applications
X-ray photos (computed tomography)
Positron emission tomography (PET)
Electron microscopy
Marginal probability distributions
Fan-beam radio telescopes
Cross-Borehole measurements in seismicsignal processing
NMR imaging
ECE 6258 Russell M. Mersereau
The Problem
Given
for several
I
= 1,2,…,
P
, estimate
x
(
u
,
v
).
Approaches:
Multidimensional Fourier transform
Radon Transform (spatial domain)
)
ˆ
(
u
p
i
ECE 6258 Russell M. Mersereau
Slices and Projections
ECE 6258 Russell M. Mersereau
Continuation
Therefore,
)
0 ,
(
)
(
μ
X
u
p
↔
μ
ν
u
)
(
0
u
p
ECE 6258 Russell M. Mersereau
Playing with the sampling intervals
By varying the sampling interval with the projectionangle, we can place samples on the same horizontaland vertical lines as the 2-D DFT.
ν
μ
ECE 6258 Russell M. Mersereau
Results (1-D Interpolation)
ECE 6258 Russell M. Mersereau
Radon Transform
We begin with the inverse Fourier transform and convert the frequency
variables to polar coordinates.
Recall that
ECE 6258 Russell M. Mersereau
Radon Transform (2)
This gives
ECE 6258 Russell M. Mersereau
Convolution Backprojection Algorithm
This suggests the following algorithm
Filter each projection by |
ω
|.
Back project at the angle of the projection.
Add all the backprojections together.
Correct the DC value.
Iterative approach
ECE 6258 Russell M. Mersereau
Results
ECE 6258 Russell M. Mersereau
Results