1.5.12.15. Plot filtering on imagesΒΆ

Demo filtering for denoising of images.

noisy, Gaussian filter, median filter, Wiener filter
# Load some data
import scipy as sp
face = sp.datasets.face(gray=True)
face = face[:512, -512:] # crop out square on right
# Apply a variety of filters
import matplotlib.pyplot as plt
import numpy as np
noisy_face = np.copy(face).astype(float)
rng = np.random.default_rng()
noisy_face += face.std() * 0.5 * rng.standard_normal(face.shape)
blurred_face = sp.ndimage.gaussian_filter(noisy_face, sigma=3)
median_face = sp.ndimage.median_filter(noisy_face, size=5)
wiener_face = sp.signal.wiener(noisy_face, (5, 5))
plt.figure(figsize=(12, 3.5))
plt.subplot(141)
plt.imshow(noisy_face, cmap=plt.cm.gray)
plt.axis("off")
plt.title("noisy")
plt.subplot(142)
plt.imshow(blurred_face, cmap=plt.cm.gray)
plt.axis("off")
plt.title("Gaussian filter")
plt.subplot(143)
plt.imshow(median_face, cmap=plt.cm.gray)
plt.axis("off")
plt.title("median filter")
plt.subplot(144)
plt.imshow(wiener_face, cmap=plt.cm.gray)
plt.title("Wiener filter")
plt.axis("off")
plt.subplots_adjust(wspace=0.05, left=0.01, bottom=0.01, right=0.99, top=0.99)
plt.show()

Total running time of the script: (0 minutes 0.472 seconds)

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