mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-01 21:15:07 +08:00
François Orieux
33aedfd9aa
This module add three function to skimage. The `wiener` function is a simple wiener deconvolution. The `unsupervised_wiener` is a more sophisticated wiener deconvolution with automatic estimation of regularisation parameters. The third function is a literal traduction in python of the rychardson lucy deconvolution of wikipedia.
39 lines
1.0 KiB
Python
39 lines
1.0 KiB
Python
import warnings
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import numpy as np
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import numpy.testing.assert_array_almost_equal
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from scipy.signal import convolve2d as conv2
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from skimage import data, deconvolution
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# Test deconvolution
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# ===========================
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test_img = data.camera().astype(np.float)
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def test_wiener():
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psf = np.ones((5, 5))
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data = conv2(test_img, psf, 'same')
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np.random.seed(0)
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data += 0.1 * data.std() * np.random.standard_normal(data.shape)
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deconvolued = deconvolution.wiener(data, psf, 25)
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numpy.testing.assert_array_almost_equal(deconvolued,
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np.load("./camera_wiener.npy"))
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def test_unsupervised_wiener():
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psf = np.ones((5, 5))
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data = conv2(test_img, psf, 'same')
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np.random.seed(0)
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data += 0.1 * data.std() * np.random.standard_normal(data.shape)
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deconvolued, _ = deconvolution.unsupervised_wiener(data, psf)
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numpy.testing.assert_array_almost_equal(deconvolued,
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np.load("./camera_unsup.npy"))
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def test_rychardson_lucy():
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return True
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