In this section, we will see how the Gaussian kernel looks like in the frequency domain in 2D and 3D plot.
The Gaussian LPF kernel spectrum in 2D
The next code block shows how to plot the spectrum of a Gaussian kernel in 2D with the log transform:
im = rgb2gray(imread('../images/lena.jpg'))gauss_kernel = np.outer(signal.gaussian(im.shape[0], 1), signal.gaussian(im.shape[1], 1))freq = fp.fft2(im)freq_kernel = fp.fft2(fp.ifftshift(gauss_kernel))pylab.imshow( (20*np.log10( 0.01 + fp.fftshift(freq_kernel))).real.astype(int), cmap='coolwarm') # 0.01 is added to keep the argument to log function always positivepylab.colorbar()pylab.show()
The following screenshot shows the output of the preceding code with ...
