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The Fourier Transform

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sin(x) A. Higher frequencies due. to sharp image variations (e.g., edges, ... (x = 0,..., N-1) 1D Discrete Fourier Transform: The Discrete Fourier Transform ... – PowerPoint PPT presentation

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Title: The Fourier Transform


1
The Fourier Transform
Jean Baptiste Joseph Fourier
2
A sum of sines and cosines

3
Higher frequencies dueto sharp image variations
(e.g., edges, noise, etc.)
4
The Continuous Fourier Transform
5
Complex Numbers
Imaginary
Z(a,b)
b
Z
?
Real
a
6
The 1D Basis Functions
1
x
1/u
  • The wavelength is 1/u .
  • The frequency is u .

7
The Continuous Fourier Transform
1D Continuous Fourier Transform
The Inverse Transform
The Transform
8
The 2D Basis Functions
V
u0, v2
u1, v2
u2, v2
u-2, v2
u-1, v2
u0, v1
u1, v1
u2, v1
u-2, v1
u-1, v1
U
u0, v0
u-2, v0
u-1, v0
u1, v0
u2, v0
u-2, v-1
u-1, v-1
u0, v-1
u1, v-1
u2, v-1
u-2, v-2
u-1, v-2
u0, v-2
u1, v-2
u2, v-2
The wavelength is . The
direction is u/v .
9
Discrete Functions
f(x)
f(n) f(x0 nDx)
f(x02Dx)
f(x03Dx)
f(x0Dx)
f(x0)
0 1 2 3 ...
N-1
x0
x0Dx
x02Dx
x03Dx
The discrete function f f(0), f(1), f(2),
, f(N-1)
10
The Discrete Fourier Transform
1D Discrete Fourier Transform
(u 0,..., N-1)
(x 0,..., N-1)
11
The Fourier Image
Fourier spectrum log(1 F(u,v))
Image f
12
Frequency Bands
Image
Fourier Spectrum
Percentage of image power enclosed in circles
(small to large) 90, 95, 98, 99,
99.5, 99.9
13
Low pass Filtering
90
95
98
99
99.5
99.9
14
Noise Removal
Noisy image
15
Noise Removal
Noisy image
Fourier Spectrum
Noise-cleaned image
16
High Pass Filtering
Original
High Pass Filtered
17
High Frequency Emphasis

Original
High Pass Filtered
18
High Frequency Emphasis
Original
High Frequency Emphasis
High Frequency Emphasis
Original
19
High Frequency Emphasis
Original
20
Properties of the Fourier Transform
Developed on the board(e.g., separability of
the 2D transform, linearity, scaling/shrinking,
derivative, rotation, shift ? phase-change,
periodicity of the discrete transform, etc.)We
also developed the Fourier Transform of various
commonly used functions, and discussed
applications which are not contained in the
slides (motion, etc.)
21
2D Image
22
Fourier Transform -- Examples
Image Domain
Frequency Domain
23
Fourier Transform -- Examples
Image Domain
Frequency Domain
24
Fourier Transform -- Examples
Image Domain
Frequency Domain
25
Fourier Transform -- Examples
Image Domain
Frequency Domain
26
Fourier Transform -- Examples
Image
Fourier spectrum
27
Fourier Transform -- Examples
Image
Fourier spectrum
28
Fourier Transform -- Examples
Image
Fourier spectrum
29
Fourier Transform -- Examples
Image
Fourier spectrum
30
Fourier Transform -- Examples
Image
Fourier spectrum
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