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doc noise filter
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@@ -571,7 +571,7 @@ def tophat(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
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return _apply(_crank8.tophat, _crank16.tophat, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y)
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def noise_filter(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
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"""Returns the noise feature as described in [1]_
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"""Returns the noise feature as described in [Hashimoto12]_
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Parameters
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----------
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@@ -579,7 +579,7 @@ def noise_filter(image, selem, out=None, mask=None, shift_x=False, shift_y=False
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Image array (uint8 array or uint16). If image is uint16, the algorithm uses max. 12bit histogram,
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an exception will be raised if image has a value > 4095
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selem : ndarray
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The neighborhood expressed as a 2-D array of 1's and 0's.
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The neighborhood expressed as a 2-D array of 1's and 0's. Central element is removed during the filtering.
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out : ndarray
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If None, a new array will be allocated.
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mask : ndarray (uint8)
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@@ -592,7 +592,7 @@ def noise_filter(image, selem, out=None, mask=None, shift_x=False, shift_y=False
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Reference
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----------
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.. [1] N. Hashimoto et al. Referenceless image quality evaluation for whole slide imaging. J Pathol Inform 2012;3:9.
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.. [Hashimoto12] N. Hashimoto et al. Referenceless image quality evaluation for whole slide imaging. J Pathol Inform 2012;3:9.
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Returns
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