wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-07-15 11:25:53 +08:00
Code Issues Packages Projects Releases Wiki Activity

Improve doc string formatting of denoise_bilateral (#2062)

Browse Source 
* Improve doc string formatting of denoise_bilateral
This commit is contained in:
Johannes Schönberger
2016-05-02 00:02:01 +03:00
committed by Egor Panfilov
parent a2d4b3cb62
commit eff310539b
1 changed files with 12 additions and 9 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/restoration/_denoise.py
+12 -9
View File
@@ -8,17 +8,18 @@ import warnings
def denoise_bilateral(image, win_size=None, sigma_color=None, sigma_spatial=1,
bins=10000, mode='constant', cval=0, multichannel=True, sigma_range=None):
bins=10000, mode='constant', cval=0, multichannel=True,
sigma_range=None):
"""Denoise image using bilateral filter.
This is an edge-preserving and noise reducing denoising filter. It averages
pixels based on their spatial closeness and radiometric similarity.
This is an edge-preserving, denoising filter. It averages pixels based on
their spatial closeness and radiometric similarity.
Spatial closeness is measured by the gaussian function of the euclidian
Spatial closeness is measured by the Gaussian function of the Euclidean
distance between two pixels and a certain standard deviation
(`sigma_spatial`).
Radiometric similarity is measured by the gaussian function of the euclidian
Radiometric similarity is measured by the Gaussian function of the Euclidean
distance between two color values and a certain standard deviation
(`sigma_color`).
@@ -28,7 +29,8 @@ def denoise_bilateral(image, win_size=None, sigma_color=None, sigma_spatial=1,
Input image, 2D grayscale or RGB.
win_size : int
Window size for filtering.
If win_size is not specified, it is calculated as max(5, 2*ceil(3*sigma_spatial)+1)
If win_size is not specified, it is calculated as
``max(5, 2 * ceil(3 * sigma_spatial) + 1)``.
sigma_color : float
Standard deviation for grayvalue/color distance (radiometric
similarity). A larger value results in averaging of pixels with larger
@@ -40,7 +42,7 @@ def denoise_bilateral(image, win_size=None, sigma_color=None, sigma_spatial=1,
Standard deviation for range distance. A larger value results in
averaging of pixels with larger spatial differences.
bins : int
Number of discrete values for gaussian weights of color filtering.
Number of discrete values for Gaussian weights of color filtering.
A larger value results in improved accuracy.
mode : {'constant', 'edge', 'symmetric', 'reflect', 'wrap'}
How to handle values outside the image borders. See
@@ -91,7 +93,8 @@ def denoise_bilateral(image, win_size=None, sigma_color=None, sigma_spatial=1,
"implemented for 2D grayscale and color images "
"only.".format(image.shape, image.shape[2]))
else:
msg = "Input image must be grayscale, RGB, or RGBA; but has shape {0}."
msg = "Input image must be grayscale, RGB, or RGBA; " \
"but has shape {0}."
warnings.warn(msg.format(image.shape))
else:
if image.ndim > 2:
@@ -110,7 +113,7 @@ def denoise_bilateral(image, win_size=None, sigma_color=None, sigma_spatial=1,
sigma_color = sigma_range
if win_size is None:
win_size = max(5, 2*int(ceil(3*sigma_spatial))+1)
win_size = max(5, 2 * int(ceil(3 * sigma_spatial)) + 1)
mode = _mode_deprecations(mode)
return _denoise_bilateral(image, win_size, sigma_color, sigma_spatial,