mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-15 11:25:53 +08:00
Improve doc strings of percentile rank filters
This commit is contained in:
Johannes Schönberger
@@ -50,17 +50,19 @@ def autolevel_percentile(image, selem, out=None, mask=None, shift_x=False,
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shift_y=False, p0=0, p1=1):
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"""Return greyscale local autolevel of an image.
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Autolevel is computed on the given structuring element. Only levels between
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percentiles [p0, p1] are used.
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This filter locally stretches the histogram of greyvalues to cover the
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entire range of values from "white" to "black".
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Only greyvalues between percentiles [p0, p1] are considered in the filter.
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Parameters
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----------
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image : ndarray (uint8, uint16)
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Image array.
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selem : ndarray
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image : 2-D array (uint8, uint16)
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Input image.
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selem : 2-D array
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The neighborhood expressed as a 2-D array of 1's and 0's.
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out : ndarray (same dtype as input)
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If None, a new array will be allocated.
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out : 2-D array (same dtype as input)
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If None, a new array is allocated.
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mask : ndarray
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Mask array that defines (>0) area of the image included in the local
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neighborhood. If None, the complete image is used (default).
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@@ -74,7 +76,7 @@ def autolevel_percentile(image, selem, out=None, mask=None, shift_x=False,
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Returns
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-------
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out : ndarray (same dtype as input image)
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out : 2-D array (same dtype as input image)
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Output image.
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"""
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@@ -86,19 +88,18 @@ def autolevel_percentile(image, selem, out=None, mask=None, shift_x=False,
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def gradient_percentile(image, selem, out=None, mask=None, shift_x=False,
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shift_y=False, p0=0, p1=1):
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"""Return greyscale local gradient of an image.
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"""Return local gradient of an image (i.e. local maximum - local minimum).
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gradient is computed on the given structuring element. Only
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levels between percentiles [p0, p1] are used.
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Only greyvalues between percentiles [p0, p1] are considered in the filter.
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Parameters
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----------
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image : ndarray (uint8, uint16)
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Image array.
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selem : ndarray
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image : 2-D array (uint8, uint16)
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Input image.
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selem : 2-D array
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The neighborhood expressed as a 2-D array of 1's and 0's.
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out : ndarray (same dtype as input)
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If None, a new array will be allocated.
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out : 2-D array (same dtype as input)
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If None, a new array is allocated.
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mask : ndarray
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Mask array that defines (>0) area of the image included in the local
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neighborhood. If None, the complete image is used (default).
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@@ -112,7 +113,7 @@ def gradient_percentile(image, selem, out=None, mask=None, shift_x=False,
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Returns
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-------
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out : ndarray (same dtype as input image)
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out : 2-D array (same dtype as input image)
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Output image.
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"""
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@@ -124,19 +125,18 @@ def gradient_percentile(image, selem, out=None, mask=None, shift_x=False,
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def mean_percentile(image, selem, out=None, mask=None, shift_x=False,
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shift_y=False, p0=0, p1=1):
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"""Return greyscale local mean of an image.
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"""Return local mean of an image.
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Mean is computed on the given structuring element. Only levels between
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percentiles [p0, p1] are used.
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Only greyvalues between percentiles [p0, p1] are considered in the filter.
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Parameters
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----------
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image : ndarray (uint8, uint16)
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Image array.
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selem : ndarray
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image : 2-D array (uint8, uint16)
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Input image.
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selem : 2-D array
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The neighborhood expressed as a 2-D array of 1's and 0's.
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out : ndarray (same dtype as input)
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If None, a new array will be allocated.
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out : 2-D array (same dtype as input)
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If None, a new array is allocated.
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mask : ndarray
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Mask array that defines (>0) area of the image included in the local
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neighborhood. If None, the complete image is used (default).
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@@ -150,7 +150,7 @@ def mean_percentile(image, selem, out=None, mask=None, shift_x=False,
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Returns
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-------
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out : ndarray (same dtype as input image)
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out : 2-D array (same dtype as input image)
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Output image.
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"""
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@@ -162,19 +162,18 @@ def mean_percentile(image, selem, out=None, mask=None, shift_x=False,
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def subtract_mean_percentile(image, selem, out=None, mask=None,
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shift_x=False, shift_y=False, p0=0, p1=1):
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"""Return greyscale local subtract_mean of an image.
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"""Return image subtracted from its local mean.
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subtract_mean is computed on the given structuring element. Only levels
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between percentiles [p0, p1] are used.
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Only greyvalues between percentiles [p0, p1] are considered in the filter.
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Parameters
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----------
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image : ndarray (uint8, uint16)
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Image array.
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selem : ndarray
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image : 2-D array (uint8, uint16)
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Input image.
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selem : 2-D array
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The neighborhood expressed as a 2-D array of 1's and 0's.
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out : ndarray (same dtype as input)
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If None, a new array will be allocated.
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out : 2-D array (same dtype as input)
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If None, a new array is allocated.
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mask : ndarray
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Mask array that defines (>0) area of the image included in the local
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neighborhood. If None, the complete image is used (default).
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@@ -188,7 +187,7 @@ def subtract_mean_percentile(image, selem, out=None, mask=None,
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Returns
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-------
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out : ndarray (same dtype as input image)
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out : 2-D array (same dtype as input image)
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Output image.
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"""
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@@ -200,19 +199,22 @@ def subtract_mean_percentile(image, selem, out=None, mask=None,
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def enhance_contrast_percentile(image, selem, out=None, mask=None,
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shift_x=False, shift_y=False, p0=0, p1=1):
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"""Return greyscale local enhance_contrast of an image.
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"""Enhance contrast of an image.
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enhance_contrast is computed on the given structuring element. Only levels
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between percentiles [p0, p1] are used.
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This replaces each pixel by the local maximum if the pixel greyvalue is
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closer to the local maximum than the local minimum. Otherwise it is
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replaced by the local minimum.
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Only greyvalues between percentiles [p0, p1] are considered in the filter.
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Parameters
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----------
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image : ndarray (uint8, uint16)
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Image array.
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selem : ndarray
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image : 2-D array (uint8, uint16)
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Input image.
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selem : 2-D array
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The neighborhood expressed as a 2-D array of 1's and 0's.
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out : ndarray (same dtype as input)
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If None, a new array will be allocated.
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out : 2-D array (same dtype as input)
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If None, a new array is allocated.
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mask : ndarray
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Mask array that defines (>0) area of the image included in the local
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neighborhood. If None, the complete image is used (default).
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@@ -226,7 +228,7 @@ def enhance_contrast_percentile(image, selem, out=None, mask=None,
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Returns
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-------
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out : ndarray (same dtype as input image)
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out : 2-D array (same dtype as input image)
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Output image.
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"""
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@@ -238,19 +240,21 @@ def enhance_contrast_percentile(image, selem, out=None, mask=None,
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def percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False,
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p0=0):
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"""Return greyscale local percentile of an image.
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"""Return local percentile of an image.
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percentile is computed on the given structuring element. Returns the value
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of the p0 lower percentile of the neighborhood value distribution.
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Returns the value of the p0 lower percentile of the local greyvalue
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distribution.
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Only greyvalues between percentiles [p0, p1] are considered in the filter.
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Parameters
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----------
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image : ndarray (uint8, uint16)
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Image array.
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selem : ndarray
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image : 2-D array (uint8, uint16)
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Input image.
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selem : 2-D array
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The neighborhood expressed as a 2-D array of 1's and 0's.
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out : ndarray (same dtype as input)
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If None, a new array will be allocated.
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out : 2-D array (same dtype as input)
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If None, a new array is allocated.
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mask : ndarray
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Mask array that defines (>0) area of the image included in the local
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neighborhood. If None, the complete image is used (default).
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@@ -263,7 +267,7 @@ def percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False,
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Returns
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-------
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out : ndarray (same dtype as input image)
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out : 2-D array (same dtype as input image)
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Output image.
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"""
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@@ -275,19 +279,21 @@ def percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False,
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def pop_percentile(image, selem, out=None, mask=None, shift_x=False,
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shift_y=False, p0=0, p1=1):
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"""Return greyscale local pop of an image.
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"""Return the local number (population) of pixels.
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pop is computed on the given structuring element. Only levels between
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percentiles [p0, p1] are used.
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The number of pixels is defined as the number of pixels which are included
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in the structuring element and the mask.
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Only greyvalues between percentiles [p0, p1] are considered in the filter.
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Parameters
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----------
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image : ndarray (uint8, uint16)
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Image array.
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selem : ndarray
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image : 2-D array (uint8, uint16)
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Input image.
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selem : 2-D array
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The neighborhood expressed as a 2-D array of 1's and 0's.
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out : ndarray (same dtype as input)
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If None, a new array will be allocated.
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out : 2-D array (same dtype as input)
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If None, a new array is allocated.
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mask : ndarray
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Mask array that defines (>0) area of the image included in the local
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neighborhood. If None, the complete image is used (default).
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@@ -301,7 +307,7 @@ def pop_percentile(image, selem, out=None, mask=None, shift_x=False,
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Returns
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-------
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out : ndarray (same dtype as input image)
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out : 2-D array (same dtype as input image)
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Output image.
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"""
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@@ -312,19 +318,18 @@ def pop_percentile(image, selem, out=None, mask=None, shift_x=False,
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def sum_percentile(image, selem, out=None, mask=None, shift_x=False,
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shift_y=False, p0=0, p1=1):
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"""Return greyscale local sum of an image.
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"""Return the local sum of pixels.
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sum is computed on the given structuring element. Only levels between
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percentiles [p0, p1] are used. Result is truncated (8bit or 16bit).
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Only greyvalues between percentiles [p0, p1] are considered in the filter.
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Parameters
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----------
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image : ndarray (uint8, uint16)
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Image array.
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selem : ndarray
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image : 2-D array (uint8, uint16)
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Input image.
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selem : 2-D array
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The neighborhood expressed as a 2-D array of 1's and 0's.
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out : ndarray (same dtype as input)
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If None, a new array will be allocated.
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out : 2-D array (same dtype as input)
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If None, a new array is allocated.
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mask : ndarray
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Mask array that defines (>0) area of the image included in the local
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neighborhood. If None, the complete image is used (default).
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@@ -338,7 +343,7 @@ def sum_percentile(image, selem, out=None, mask=None, shift_x=False,
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Returns
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-------
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out : ndarray (same dtype as input image)
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out : 2-D array (same dtype as input image)
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Output image.
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"""
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@@ -349,21 +354,21 @@ def sum_percentile(image, selem, out=None, mask=None, shift_x=False,
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def threshold_percentile(image, selem, out=None, mask=None, shift_x=False,
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shift_y=False, p0=0):
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"""Return greyscale local threshold of an image.
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"""Local threshold of an image.
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threshold is computed on the given structuring element. Returns
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thresholded image such that pixels having a higher value than the the p0
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percentile of the neighborhood value distribution are set to 2^nbit-1
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(e.g. 255 for 8bit image).
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The resulting binary mask is True if the greyvalue of the center pixel is
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greater than the local mean.
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Only greyvalues between percentiles [p0, p1] are considered in the filter.
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Parameters
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----------
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image : ndarray (uint8, uint16)
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Image array.
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selem : ndarray
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image : 2-D array (uint8, uint16)
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Input image.
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selem : 2-D array
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The neighborhood expressed as a 2-D array of 1's and 0's.
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out : ndarray (same dtype as input)
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If None, a new array will be allocated.
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out : 2-D array (same dtype as input)
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If None, a new array is allocated.
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mask : ndarray
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Mask array that defines (>0) area of the image included in the local
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neighborhood. If None, the complete image is used (default).
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@@ -374,7 +379,7 @@ def threshold_percentile(image, selem, out=None, mask=None, shift_x=False,
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p0 : float in [0, ..., 1]
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Set the percentile value.
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out : ndarray (same dtype as input image)
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out : 2-D array (same dtype as input image)
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Output image.
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local threshold : ndarray (same dtype as input)
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The result of the local threshold.
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