Code covered by the BSD License
analysis(f, J, alpha, tau) % signal is first prefiltered, and then a J-level wavelet decomposition
analysis(inImg, J, alpha,... % First, project the image into the four (tensor) approximation space.
autocorr(M, alpha) % computes the autocorrelation filter A(z) for the fractional B-spline.
autocorr(M, alpha) % computes the autocorrelation filter A(z) for the fractional B-spline.
displayFigures (inImg, w,... % Plots the original and the reconstructed images, and the modulus of the
displayResults(f, recon, w) % display the original and the reconstructed signal, the real and the
exception( f ) % Checks for inconsistencies.
exception(f, J) % check and correct for inconsistency.
filters(M, alpha, tau, flag) % sets up the multiresolution spline filters.
filters(M, alpha, tau, tag) % Computes the analysis and synthesis filters corresponding to the
generate.m
generateGaborWavelets.m
postfilter(Y, L, alpha, t... % Inverts the prefiltering operation.
prefilter(im0, alpha, tau... % projects the image onto the four different approximation spaces used in
projectionFilters(M, alph... % projects the signal onto the four 'matched' approximtion spaces.
projectionFilters(M, alph... % projects the signal onto the two 'matched' approximtion spaces.
synthesis(lowpass, w, J, ... % reconstructs the signal from the lowpass signal and the complex wavelet
synthesis(lowpass, w, J, ... % reconstructs the image from the lowpass signals, and the complex wavelet
demo.m
demo.m
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Multiresolution Gabor-like transforms
by
Kunal Chaudhury
11 May 2012
(Updated
14 May 2012 )
Matlab implementation of the multiresolution Gabor filters in 1 and 2 dimensions.
autocorr(M, alpha)
function [A, A2] = autocorr(M, alpha)
%
% computes the autocorrelation filter A(z) for the fractional B-spline.
% A2(z) = A(z^2).
%
nu = (0: 1: M-1)/M;
% N-term approximation
N = 150;
A = zeros(1, M);
for n = -N : 1 : N
A = A + abs(sinc(nu + n)).^(2*alpha+2);
end
A2 = [A A];
A2 = A2(1 : 2 : length(A2));
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