EE 4780 2D Fourier Transform.

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Presentation transcript:

EE 4780 2D Fourier Transform

Fourier Transform What is ahead? 1D Fourier Transform of continuous signals 2D Fourier Transform of continuous signals 2D Fourier Transform of discrete signals 2D Discrete Fourier Transform (DFT) Bahadir K. Gunturk

Fourier Transform: Concept A signal can be represented as a weighted sum of sinusoids. Fourier Transform is a change of basis, where the basis functions consist of sines and cosines (complex exponentials). Bahadir K. Gunturk

Fourier Transform Cosine/sine signals are easy to define and interpret. However, it turns out that the analysis and manipulation of sinusoidal signals is greatly simplified by dealing with related signals called complex exponential signals. A complex number has real and imaginary parts: z = x + j*y A complex exponential signal: r*exp(j*a) =r*cos(a) + j*r*sin(a) Bahadir K. Gunturk

Fourier Transform: 1D Cont. Signals Fourier Transform of a 1D continuous signal “Euler’s formula” Inverse Fourier Transform Bahadir K. Gunturk

Fourier Transform: 2D Cont. Signals Fourier Transform of a 2D continuous signal Inverse Fourier Transform F and f are two different representations of the same signal. Bahadir K. Gunturk

Fourier Transform: Properties Remember the impulse function (Dirac delta function) definition Fourier Transform of the impulse function Bahadir K. Gunturk

Fourier Transform: Properties Fourier Transform of 1 Take the inverse Fourier Transform of the impulse function Bahadir K. Gunturk

Fourier Transform: Properties Fourier Transform of cosine Bahadir K. Gunturk

Examples Magnitudes are shown Bahadir K. Gunturk

Examples Bahadir K. Gunturk

Fourier Transform: Properties Linearity Shifting Modulation Convolution Multiplication Separable functions Bahadir K. Gunturk

Fourier Transform: Properties Separability 2D Fourier Transform can be implemented as a sequence of 1D Fourier Transform operations. Bahadir K. Gunturk

Fourier Transform: Properties Energy conservation Bahadir K. Gunturk

Fourier Transform: 2D Discrete Signals Fourier Transform of a 2D discrete signal is defined as where Inverse Fourier Transform Bahadir K. Gunturk

Fourier Transform: Properties Periodicity: Fourier Transform of a discrete signal is periodic with period 1. 1 1 Arbitrary integers Bahadir K. Gunturk

Fourier Transform: Properties Linearity, shifting, modulation, convolution, multiplication, separability, energy conservation properties also exist for the 2D Fourier Transform of discrete signals. Bahadir K. Gunturk

Fourier Transform: Properties Linearity Shifting Modulation Convolution Multiplication Separable functions Energy conservation Bahadir K. Gunturk

Fourier Transform: Properties Define Kronecker delta function Fourier Transform of the Kronecker delta function Bahadir K. Gunturk

Fourier Transform: Properties Fourier Transform of 1 To prove: Take the inverse Fourier Transform of the Dirac delta function and use the fact that the Fourier Transform has to be periodic with period 1. Bahadir K. Gunturk

Impulse Train Define a comb function (impulse train) as follows where M and N are integers Bahadir K. Gunturk

Impulse Train Fourier Transform of an impulse train is also an impulse train: Bahadir K. Gunturk

Impulse Train Bahadir K. Gunturk

Impulse Train In the case of continuous signals: Bahadir K. Gunturk

Impulse Train Bahadir K. Gunturk

Sampling Bahadir K. Gunturk

Sampling No aliasing if Bahadir K. Gunturk

Sampling If there is no aliasing, the original signal can be recovered from its samples by low-pass filtering. Bahadir K. Gunturk

Sampling Aliased Bahadir K. Gunturk

Sampling Anti-aliasing filter Bahadir K. Gunturk

Sampling Without anti-aliasing filter: With anti-aliasing filter: Bahadir K. Gunturk

Anti-Aliasing a=imread(‘barbara.tif’); Bahadir K. Gunturk

Anti-Aliasing a=imread(‘barbara.tif’); b=imresize(a,0.25); c=imresize(b,4); Bahadir K. Gunturk

Anti-Aliasing a=imread(‘barbara.tif’); b=imresize(a,0.25); c=imresize(b,4); H=zeros(512,512); H(256-64:256+64, 256-64:256+64)=1; Da=fft2(a); Da=fftshift(Da); Dd=Da.*H; Dd=fftshift(Dd); d=real(ifft2(Dd)); Bahadir K. Gunturk

Sampling Bahadir K. Gunturk

Sampling No aliasing if and Bahadir K. Gunturk

Interpolation Ideal reconstruction filter: Bahadir K. Gunturk

Ideal Reconstruction Filter Bahadir K. Gunturk