From 085be65e83148a09b98ae5d0df3fb0bb1099d5da Mon Sep 17 00:00:00 2001 From: Steven Silvester Date: Mon, 13 Jul 2015 17:00:13 -0500 Subject: [PATCH] Remove use of view_as_window and fix docstring --- skimage/exposure/_adapthist.py | 12 +++--------- 1 file changed, 3 insertions(+), 9 deletions(-) diff --git a/skimage/exposure/_adapthist.py b/skimage/exposure/_adapthist.py index 3b021ce5..343f71b3 100644 --- a/skimage/exposure/_adapthist.py +++ b/skimage/exposure/_adapthist.py @@ -19,7 +19,6 @@ import numpy as np from .. import img_as_float, img_as_uint from ..color.adapt_rgb import adapt_rgb, hsv_value from ..exposure import rescale_intensity -from ..util import view_as_windows from .._shared.utils import skimage_deprecation, warnings NR_OF_GREY = 2 ** 14 # number of grayscale levels to use in CLAHE algorithm @@ -44,7 +43,7 @@ def equalize_adapthist(image, ntiles_x=8, ntiles_y=8, clip_limit=0.01, sidelength given by this value. ntiles_x : int, optional (deprecated in favor of ``kernel_size``) Number of tile regions in the X direction (horizontal). - ntiles_y : int, optional (deprecated if favor of ``kernel_size``) + ntiles_y : int, optional (deprecated in favor of ``kernel_size``) Number of tile regions in the Y direction (vertical). clip_limit : float: optional Clipping limit, normalized between 0 and 1 (higher values give more @@ -131,8 +130,6 @@ def _clahe(image, kernel_size, clip_limit, nbins=128): row_step = int(np.floor(image.shape[0] / nr)) col_step = int(np.floor(image.shape[1] / nc)) - img_view = view_as_windows(image, kernel_size, (row_step, col_step)) - bin_size = 1 + NR_OF_GREY // nbins lut = np.arange(NR_OF_GREY) lut //= bin_size @@ -142,11 +139,8 @@ def _clahe(image, kernel_size, clip_limit, nbins=128): # Calculate greylevel mappings for each contextual region for r in range(nr): for c in range(nc): - if r < (nr - 1) and c < (nc - 1): - sub_img = img_view[r, c] - else: - sub_img = image[r * row_step: (r + 1) * row_step, - c * col_step: (c + 1) * col_step] + sub_img = image[r * row_step: (r + 1) * row_step, + c * col_step: (c + 1) * col_step] if clip_limit > 0.0: # Calculate actual cliplimit clim = int(clip_limit * sub_img.size / nbins)