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Digital Image Processing Homework II Fast Fourier Transform 2012/03/28 Chih-Hung Lu ( 呂志宏 ) Visual Communications Laboratory Department of Communication Engineering National Central University ChungLi, Taiwan
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The Goal of This Homework Implement Fast Fourier Transform. Implement Inverse Fast Fourier Transform. Implement Notch Filter.
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Work Chart 3 FFT Filtering (Notch Filter) IFFT
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To compute a discrete Fourier transform: N: number of pixel f(x): value of pixel x: pixel position F(u): value of frequency u: frequency Rewritten as: where Fast Fourier Transform(1/3) 4
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Fast Fourier Transform(2/3) Assume N= 2 n, Let N=2M. 5
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Fast Fourier Transform(3/3) 6 Because (e jx = cos(x) + j sin(x))
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Fast Fourier Transform(8 points) 7
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Inverse Fast Fourier Transform 8 To compute a Inverse Fourier transform: N: number of pixel f(x): value of pixel x: pixel position F(u): value of frequency u: frequency where
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Notch Filter 9 Ideal Notch Reject Filter: H: Filter Set F(0,0) to zero & leave all other frequency components of the Fourier transform untouched.
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Display of Frequency Spectrum 10 Modulation in space domain: Moving (0,0) to the central in image. Log transformation Example:
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Grading FFT (3 points) Filtering (3 points) IFFT (2 points) Report (2 points) Computation complexity (Bonus 1 points) Other properties (Bonus 1 points)
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Demo Schedule Thursday night, 19 April, 2012. - Begin around at 19:00 at R3-307.(VCLab) NOTE: We will use another image to test your code. The details will be announced on our course website. ( http://140.115.156.251/vclab/html/course/DIP2012.html )
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References Paul Heckbert, Fourier Transforms and the Fast Fourier Transform (FFT) Algorithm www.cs.cmu.edu/afs/andrew/.../fourier/fouri er.pdf www.cs.cmu.edu/afs/andrew/.../fourier/fouri er.pdf J.W. Cooley and J.W. Tukey, “An algorithm for the machine calculation of complex Fourier series”, Math. Computation, 19:297-301, 1965.
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