The following code block shows how to reject a bunch of high frequencies and implement an LPF to attenuate noise (which corresponds to high-frequency components) from the image:
# Copy the original spectrum and truncate coefficients.# Define the fraction of coefficients (in each direction) to keep askeep_fraction = 0.1im_fft2 = im_fft.copy()# Set r and c to the number of rows and columns of the array.r, c = im_fft2.shape# Set all rows to zero with indices between r*keep_fraction and r*(1-keep_fraction)im_fft2[int(r*keep_fraction):int(r*(1-keep_fraction))] = 0# Similarly with the columnsim_fft2[:, int(c*keep_fraction):int(c*(1-keep_fraction))] = 0pylab.figure(), plot_spectrum(fftpack.fftshift(im_fft2)),pylab.title('Filtered Spectrum') ...
