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Fundamentals of Twodimensional Signals and Systems
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according to eqn algorithm amplitude analysis approximately areas assumed bandwidth calculated characteristics complex constant convolution corresponding spatial corresponding spectrum defined in eqn Dirac direction discrete Fourier transform discrete signal edge model elements equation error example fast Fourier transform Figure filter coefficients function f(m,n Gaussian Gaussian function gradient image gradient operators Hankel transform histogram image pixels image restoration image window impulse response intensity values interval inverse filter inverse transform Karhunen-Loeve transform low-pass filter matrix maximum model edge multiplications noise signal obtained one-dimensional operator window optimization optimum original image parameters patterns picture signals power spectrum processing pulse recursive filter regions representation represented rotationally symmetric sampling segmentation sequence shown in Fig signal f(m,n signal theory signal-dependent simulation space-variant spatial domain spatial frequency domain spatial frequency spectrum spatial functions spectra spectral power density superimposed systems theory template test image theorem transfer function variables vector Wiener filter zero