This function from the scipy ndimage module implements a multi-dimensional Gaussian Fourier filter. The frequency array is multiplied with the Fourier transform of a Gaussian kernel of a given size.
The next code block demonstrates how to use the LPF (weighted average filter) to blur the lena grayscale image:
import numpy.fft as fpfig, (axes1, axes2) = pylab.subplots(1, 2, figsize=(20,10))pylab.gray() # show the result in grayscaleim = np.mean(imread('../images/lena.jpg'), axis=2)freq = fp.fft2(im)freq_gaussian = ndimage.fourier_gaussian(freq, sigma=4)im1 = fp.ifft2(freq_gaussian)axes1.imshow(im), axes1.axis('off'), axes2.imshow(im1.real) # the imaginary part is an artifactaxes2.axis('off')pylab.show()
The following ...
