Hands-On Image Processing with Python

Frequency domain Gaussian blur filter with scipy signal.fftconvolve()

The following code block shows how the SciPy signal module's fftconvolve() function can be used to run the convolution in the frequency domain (internally by just a multiplication and the convolution theorem):

im = np.mean(misc.imread('../images/mandrill.jpg'), axis=2) print(im.shape)# (224, 225)gauss_kernel = np.outer(signal.gaussian(11, 3), signal.gaussian(11, 3)) # 2D Gaussian kernel of size 11x11 with σ = 3im_blurred = signal.fftconvolve(im, gauss_kernel, mode='same')fig, (ax_original, ax_kernel, ax_blurred) = pylab.subplots(1, 3, figsize=(20,8))ax_original.imshow(im, cmap='gray')ax_original.set_title('Original', size=20)ax_original.set_axis_off()ax_kernel.imshow(gauss_kernel) ...