Let's first detect edges from a grayscale cameraman.jpg image using convolution with the Laplace kernel and also blur an image using the box kernel:
im = rgb2gray(imread('../image s/cameraman.jpg')).astype(float)print(np.max(im))# 1.0print(im.shape)# (225, 225)blur_box_kernel = np.ones((3,3)) / 9edge_laplace_kernel = np.array([[0,1,0],[1,-4,1],[0,1,0]])im_blurred = signal.convolve2d(im, blur_box_kernel)im_edges = np.clip(signal.convolve2d(im, edge_laplace_kernel), 0, 1)fig, axes = pylab.subplots(ncols=3, sharex=True, sharey=True, figsize=(18, 6))axes[0].imshow(im, cmap=pylab.cm.gray)axes[0].set_title('Original Image', size=20)axes[1].imshow(im_blurred, cmap=pylab.cm.gray)axes[1].set_title('Box Blur', ...
