Unsharp masking

gistfile1.txt

from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from skimage import io, img_as_float


def median_filter(A, filter_size):
    rows = np.shape(A)[0]
    columns = np.shape(A)[1]
    half_length = int((filter_size-1)/2)

    pad_A = np.concatenate([np.zeros((rows, half_length)), A, np.zeros((rows, half_length))], axis=1)
    pad_A = np.concatenate([np.zeros((half_length, columns+2*half_length)), pad_A, np.zeros((half_length, columns+2*half_length))], axis=0)
    
    B = np.zeros_like(A)
    for i in xrange(0, rows):
        for j in xrange(0, columns):
            B[i, j] = np.median(pad_A[i:filter_size + i, j:filter_size + j])

    return B
    

def unsharp_masking(A):
    smoothed = median_filter(A, 3)
    mask = A - smoothed 
    sharpened = A + mask

    return sharpened


A = io.imread('wrinkled_face.jpg', plugin='pil')
A = 0.3*A[:, :, 0] + 0.59*A[:, :, 1] + 0.11*A[:, :, 2]
out = unsharp_masking(A)

f, (ax0, ax1) = plt.subplots(1, 2)
f.tight_layout()

ax0.imshow(A, cmap=plt.cm.gray)
ax0.set_title('Input Image')

ax1.imshow(out, cmap=plt.cm.gray)
ax1.set_title('Unsharp masking applied to input image, filter size = 5')

plt.show()