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Fix typo in doc string
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@@ -98,7 +98,7 @@ def denoise_bilateral(image, Py_ssize_t win_size=5, sigma_range=None,
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"""
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image = np.atleast_3d(img_as_float(image))
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# if image.max() is 0, then dist_scale can have an unverified value
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# and color_lut[<int>(dist * dist_scale)] may cause a segmentation fault
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# so we verify we have a positive image and that the max is not 0.0.
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@@ -112,7 +112,7 @@ def denoise_bilateral(image, Py_ssize_t win_size=5, sigma_range=None,
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Py_ssize_t window_ext = (win_size - 1) / 2
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double max_value
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cnp.ndarray[dtype=cnp.double_t, ndim=3, mode='c'] cimage
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cnp.ndarray[dtype=cnp.double_t, ndim=3, mode='c'] out
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@@ -136,12 +136,12 @@ def denoise_bilateral(image, Py_ssize_t win_size=5, sigma_range=None,
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csigma_range = sigma_range
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max_value = image.max()
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if max_value == 0.0:
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raise ValueError("The maximum value found in the image was 0.")
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cimage = np.ascontiguousarray(image)
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out = np.zeros((rows, cols, dims), dtype=np.double)
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image_data = <double*>cimage.data
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out_data = <double*>out.data
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@@ -224,8 +224,8 @@ def denoise_tv_bregman(image, double weight, int max_iter=100, double eps=1e-3,
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max_iter: int, optional
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Maximal number of iterations used for the optimization.
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isotropic: boolean, optimal
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Switch between isotropic and anisotropic tv denoising
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isotropic: boolean, optional
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Switch between isotropic and anisotropic TV denoising.
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Returns
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-------
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@@ -241,7 +241,7 @@ def denoise_tv_bregman(image, double weight, int max_iter=100, double eps=1e-3,
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.. [3] Pascal Getreuer, "Rudin–Osher–Fatemi Total Variation Denoising
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using Split Bregman" in Image Processing On Line on 2012–05–19,
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http://www.ipol.im/pub/art/2012/g-tvd/article_lr.pdf
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.. [4] http://www.math.ucsb.edu/~cgarcia/UGProjects/BregmanAlgorithms_JacquelineBush.pdf
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.. [4] http://www.math.ucsb.edu/~cgarcia/UGProjects/BregmanAlgorithms_JacquelineBush.pdf
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"""
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