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synced 2026-08-13 12:40:24 +08:00
Use common spelling for greylevel
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@@ -62,7 +62,7 @@ def mean(np.ndarray[np.uint16_t, ndim=2] image,
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np.ndarray[np.uint8_t, ndim=2] mask=None,
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np.ndarray[np.uint16_t, ndim=2] out=None,
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char shift_x=0, char shift_y=0, int bitdepth=8, int s0=1, int s1=1):
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"""average gray level (clipped on uint8)
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"""average greylevel (clipped on uint8)
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"""
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_core16(kernel_mean, image, selem, mask, out, shift_x, shift_y,
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bitdepth, 0., 0., s0, s1)
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@@ -14,7 +14,7 @@ maximum value present in the image.
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The pixel neighborhood is defined by:
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* the given structuring element
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* an interval [g-s0,g+s1] in gray level around g the processed pixel gray level
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* an interval [g-s0,g+s1] in greylevel around g the processed pixel greylevel
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The kernel is flat (i.e. each pixel belonging to the neighborhood contributes
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equally).
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@@ -78,9 +78,9 @@ def bilateral_mean(image, selem, out=None, mask=None, shift_x=False,
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Spatial closeness is measured by considering only the local pixel
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neighborhood given by a structuring element (selem).
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Radiometric similarity is defined by the gray level interval [g-s0,g+s1]
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where g is the current pixel gray level. Only pixels belonging to the
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structuring element AND having a gray level inside this interval are
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Radiometric similarity is defined by the greylevel interval [g-s0,g+s1]
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where g is the current pixel greylevel. Only pixels belonging to the
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structuring element AND having a greylevel inside this interval are
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averaged. Return greyscale local bilateral_mean of an image.
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Parameters
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@@ -447,7 +447,7 @@ def modal(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
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def morph_contr_enh(image, selem, out=None, mask=None, shift_x=False,
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shift_y=False):
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"""Enhance an image replacing each pixel by the local maximum if pixel
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graylevel is closest to maximimum than local minimum OR local minimum
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greylevel is closest to maximimum than local minimum OR local minimum
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otherwise.
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Parameters
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