Note
Click here to download the full example code
2.6.8.15. 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/sphx_glr_plot_denoising_001.png](http://scipy-lectures.org/_images/sphx_glr_plot_denoising_001.png)
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 script: ( 0 minutes 0.046 seconds)