<gh_stars>1000+
"""
Image denoising
================

This example demoes image denoising on a Racoon face.
"""

import numpy as np
import scipy
import scipy.misc
from scipy import ndimage
import matplotlib.pyplot as plt

f = scipy.misc.face(gray=True)
f = f[230:290, 220:320]

noisy = f + 0.4*f.std()*np.random.random(f.shape)

gauss_denoised = ndimage.gaussian_filter(noisy, 2)
med_denoised = ndimage.median_filter(noisy, 3)


plt.figure(figsize=(12,2.8))

plt.subplot(131)
plt.imshow(noisy, cmap=plt.cm.gray, vmin=40, vmax=220)
plt.axis('off')
plt.title('noisy', fontsize=20)
plt.subplot(132)
plt.imshow(gauss_denoised, cmap=plt.cm.gray, vmin=40, vmax=220)
plt.axis('off')
plt.title('Gaussian filter', fontsize=20)
plt.subplot(133)
plt.imshow(med_denoised, cmap=plt.cm.gray, vmin=40, vmax=220)
plt.axis('off')
plt.title('Median filter', fontsize=20)

plt.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9, bottom=0, left=0,
                    right=1)
plt.show()

"""
Image denoising
================

This example demoes image denoising on a Racoon face.
"""

import numpy as np
import scipy
import scipy.misc
from scipy import ndimage
import matplotlib.pyplot as plt

f = scipy.misc.face(gray=True)
f = f[230:290, 220:320]

noisy = f + 0.4*f.std()*np.random.random(f.shape)

gauss_denoised = ndimage.gaussian_filter(noisy, 2)
med_denoised = ndimage.median_filter(noisy, 3)


plt.figure(figsize=(12,2.8))

plt.subplot(131)
plt.imshow(noisy, cmap=plt.cm.gray, vmin=40, vmax=220)
plt.axis('off')
plt.title('noisy', fontsize=20)
plt.subplot(132)
plt.imshow(gauss_denoised, cmap=plt.cm.gray, vmin=40, vmax=220)
plt.axis('off')
plt.title('Gaussian filter', fontsize=20)
plt.subplot(133)
plt.imshow(med_denoised, cmap=plt.cm.gray, vmin=40, vmax=220)
plt.axis('off')
plt.title('Median filter', fontsize=20)

plt.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9, bottom=0, left=0,
                    right=1)
plt.show()
Image denoising ================  This example demoes image denoising on a Racoon face.