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Some improvements to new deconvolution code
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committed by
François Orieux
parent
17cc22802c
commit
e25ccf61f6
@@ -1,38 +1,33 @@
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import warnings
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from os.path import abspath, dirname, join as pjoin
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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
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from skimage.data import camera
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from skimage import deconvolution
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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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test_img = 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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data = convolve2d(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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path = pjoin(dirname(abspath(__file__)), 'camera_wiener.npy')
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np.testing.assert_array_almost_equal(deconvolued, np.load(path))
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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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data = convolve2d(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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path = pjoin(dirname(abspath(__file__)), 'camera_unsup.npy')
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np.testing.assert_array_almost_equal(deconvolued, np.load(path))
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def test_rychardson_lucy():
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def test_richardson_lucy():
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return True
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