Denoising an image with the median filter

This example shows the original image, the noisy image, the denoised one (with the median filter) and the difference between the two.

../../../_images/plot_denoising_1.png

Python source code: plot_denoising.py

import numpy as np

from scipy import ndimage

import matplotlib.pyplot as plt



im = np.zeros((20, 20))

im[5:-5, 5:-5] = 1

im = ndimage.distance_transform_bf(im)

im_noise = im + 0.2*np.random.randn(*im.shape)



im_med = ndimage.median_filter(im_noise, 3)



plt.figure(figsize=(16, 5))



plt.subplot(141)

plt.imshow(im, interpolation='nearest')

plt.axis('off')

plt.title('Original image', fontsize=20)

plt.subplot(142)

plt.imshow(im_noise, interpolation='nearest', vmin=0, vmax=5)

plt.axis('off')

plt.title('Noisy image', fontsize=20)

plt.subplot(143)

plt.imshow(im_med, interpolation='nearest', vmin=0, vmax=5)

plt.axis('off')

plt.title('Median filter', fontsize=20)

plt.subplot(144)

plt.imshow(np.abs(im - im_med), cmap=plt.cm.hot, interpolation='nearest')

plt.axis('off')

plt.title('Error', fontsize=20)





plt.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9, bottom=0, left=0,

                    right=1)



plt.show()

Total running time of the example: 0.13 seconds ( 0 minutes 0.13 seconds)