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Merge pull request #2190 from stsievert/wavelet-denoise-v2

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ENH: Implements wavelet denoising (from #1833)
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Josh Warner
2016-08-05 00:03:12 -05:00
committed by GitHub
parent 0852e3b171 13490a64ac
commit 0ea2a3423b
6 changed files with 175 additions and 12 deletions
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doc/examples/filters/plot_denoise.py
+17 -11
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@@ -29,16 +29,16 @@ import numpy as np
import matplotlib.pyplot as plt
from skimage import data, img_as_float
from skimage.restoration import denoise_tv_chambolle, denoise_bilateral
from skimage.restoration import denoise_tv_chambolle, denoise_bilateral, denoise_wavelet
from skimage.util import random_noise
astro = img_as_float(data.astronaut())
astro = astro[220:300, 220:320]
noisy = astro + 0.6 * astro.std() * np.random.random(astro.shape)
noisy = np.clip(noisy, 0, 1)
noisy = random_noise(astro, var=(0.6 * astro.std())**2)
fig, ax = plt.subplots(nrows=2, ncols=3, figsize=(8, 5), sharex=True,
fig, ax = plt.subplots(nrows=2, ncols=4, figsize=(8, 5), sharex=True,
sharey=True, subplot_kw={'adjustable': 'box-forced'})
plt.gray()
@@ -52,16 +52,22 @@ ax[0, 1].set_title('TV')
ax[0, 2].imshow(denoise_bilateral(noisy, sigma_color=0.05, sigma_spatial=15))
ax[0, 2].axis('off')
ax[0, 2].set_title('Bilateral')
ax[0, 3].imshow(denoise_wavelet(noisy, sigma=0.4*astro.std()))
ax[0, 3].axis('off')
ax[0, 3].set_title('Wavelet')
ax[1, 0].imshow(denoise_tv_chambolle(noisy, weight=0.2, multichannel=True))
ax[1, 0].axis('off')
ax[1, 0].set_title('(more) TV')
ax[1, 1].imshow(denoise_bilateral(noisy, sigma_color=0.1, sigma_spatial=15))
ax[1, 1].imshow(denoise_tv_chambolle(noisy, weight=0.2, multichannel=True))
ax[1, 1].axis('off')
ax[1, 1].set_title('(more) Bilateral')
ax[1, 2].imshow(astro)
ax[1, 1].set_title('(more) TV')
ax[1, 2].imshow(denoise_bilateral(noisy, sigma_color=0.1, sigma_spatial=15))
ax[1, 2].axis('off')
ax[1, 2].set_title('original')
ax[1, 2].set_title('(more) Bilateral')
ax[1, 3].imshow(denoise_wavelet(noisy, sigma=0.6*astro.std()))
ax[1, 3].axis('off')
ax[1, 3].set_title('(more) Wavelet')
ax[1, 0].imshow(astro)
ax[1, 0].axis('off')
ax[1, 0].set_title('original')
fig.tight_layout()