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Digital Image Processing Chapter 4: Image Enhancement in the Frequency Domain
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Background The French mathematiian Jean Baptiste Joseph Fourier Born in 1768 Published Fourier series in 1822 Fourier ’ s ideas were met with skepticism Fourier series Any periodical function can be expressed as the sum of sines and/or cosines of different frequencies, each multiplied by a different coefficient
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Fourier transform Functions can be expressed as the integral of sines and/or cosines multiplied by a weighting function Functions expressed in either a Fourier series or transform can be reconstructed completely via an inverse process with no loss of information
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Applications Heat diffusion Fast Fourier transform (FFT) developed in the late 1950s
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Introduction to the Fourier Transform and the Frequency Domain The one-dimensional Fourier transform and its inverse Fourier transform Inverse Fourier transform
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Two variables Fourier transform Inverse Fourier transform
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Discrete Fourier transform (DFT) Original variable Transformed variable
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DFT The discrete Fourier transform and its inverse always exist f(x) is finite in the book
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Sines and cosines
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Time domain Time components Frequency domain Frequency components
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Fourier transform and a glass prism Prism Separates light into various color components, each depending on its wavelength (or frequency) content Fourier transform Separates a function into various components, also based on frequency content Mathematical prism
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Polar coordinates Real part Imaginary part
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Magnitude or spectrum Phase angle or phase spectrum Power spectrum or spectral density
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Samples
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Some references http://local.wasp.uwa.edu.au/~pbourk e/other/dft/ http://local.wasp.uwa.edu.au/~pbourk e/other/dft/ http://homepages.inf.ed.ac.uk/rbf/HIP R2/fourier.htm http://homepages.inf.ed.ac.uk/rbf/HIP R2/fourier.htm
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Examples test_fft.c test_fft.c fft.h fft.h fft.c fft.c Fig4.03(a).bmp Fig4.03(a).bmp test_fig2.bmp test_fig2.bmp
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