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University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier Transforms.

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Presentation on theme: "University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier Transforms."— Presentation transcript:

1 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier Transforms

2 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier series To go from f(  ) to f(t) substitute To deal with the first basis vector being of length 2  instead of , rewrite as

3 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier series The coefficients become

4 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier series Alternate forms where

5 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Complex exponential notation Euler’s formula Phasor notation:

6 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Euler’s formula Taylor series expansions Even function ( f(x) = f(-x) ) Odd function ( f(x) = -f(-x) )

7 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Complex exponential form Consider the expression So Since a n and b n are real, we can let and get

8 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Complex exponential form Thus So you could also write

9 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier transform We now have Let’s not use just discrete frequencies, n  0, we’ll allow them to vary continuously too We’ll get there by setting t 0 =-T/2 and taking limits as T and n approach 

10 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier transform

11 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier transform So we have (unitary form, angular frequency) Alternatives (Laplace form, angular frequency)

12 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier transform Ordinary frequency

13 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier transform Some sufficient conditions for application Dirichlet conditions f(t) has finite maxima and minima within any finite interval f(t) has finite number of discontinuities within any finite interval Square integrable functions (L 2 space) Tempered distributions, like Dirac delta

14 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Fourier transform Complex form – orthonormal basis functions for space of tempered distributions

15 University of Texas at Austin CS395T - Advanced Image Synthesis Spring 2006 Don Fussell Convolution theorem Theorem Proof (1)


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