Python Image Processing Cookbook

How to do it...

The following steps need to be performed:

1. Define the normalize() function to implement min-max normalization in an image:

def normalize(img):    return (img-np.min(img))/(np.max(img)-np.min(img))

2. Implement the sketch() function that takes an image and the extracted edges as input:

def sketch(img, edges):    output = np.multiply(img, edges)    output[output>1]=1    output[edges==1]=1    return output

3. Implement a function to extract the edges from an image with anisotropic diffusion:

def edges_with_anisotropic_diffusion(img, niter=100, kappa=10, gamma=0.1):    output = img - anisotropic_diffusion(img, niter=niter, \            kappa=kappa, gamma=gamma, voxelspacing=None, \            option=1)    output[output > 0] = 1    output[output < 0] = 0    return output