From c73d1c98e015f060c9be3b93e985708afe46e8ed Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= Date: Tue, 7 Oct 2014 08:38:26 -0400 Subject: [PATCH] Clarify that uint16 images are only faster up to a certain bit depth --- skimage/morphology/grey.py | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/skimage/morphology/grey.py b/skimage/morphology/grey.py index 1f1c45d4..6c901b4a 100644 --- a/skimage/morphology/grey.py +++ b/skimage/morphology/grey.py @@ -8,6 +8,7 @@ from . import cmorph __all__ = ['erosion', 'dilation', 'opening', 'closing', 'white_tophat', 'black_tophat'] + @default_fallback def erosion(image, selem=None, out=None, shift_x=False, shift_y=False): """Return greyscale morphological erosion of an image. @@ -37,9 +38,9 @@ def erosion(image, selem=None, out=None, shift_x=False, shift_y=False): Notes ----- - For `uint8` and `uint16` data, the lower algorithm complexity makes the - `skimage.filter.rank.minimum` function more efficient for larger images - and structuring elements. + For `uint8` (and `uint16` up to a certain bit-depth) data, the lower + algorithm complexity makes the `skimage.filter.rank.minimum` function more + efficient for larger images and structuring elements. Examples -------- @@ -98,9 +99,9 @@ def dilation(image, selem=None, out=None, shift_x=False, shift_y=False): Notes ----- - For `uint8` and `uint16` data, the lower algorithm complexity makes the - `skimage.filter.rank.maximum` function more efficient for larger images - and structuring elements. + For `uint8` (and `uint16` up to a certain bit-depth) data, the lower + algorithm complexity makes the `skimage.filter.rank.minimum` function more + efficient for larger images and structuring elements. Examples --------