wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-07-19 11:27:45 +08:00
Code Issues Packages Projects Releases Wiki Activity

Merge pull request #1845 from grlee77/tv_weight_fix

Browse Source 
Use appropriate weights in tv_denoise_chambolle
This commit is contained in:
Emmanuelle Gouillart
2015-12-23 19:53:51 +01:00
parent d6105a0fe4 3f5aa73eb4
commit fb9fdec7db
2 changed files with 10 additions and 10 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/restoration/_denoise.py
+4 -4
View File
@@ -31,7 +31,7 @@ def denoise_bilateral(image, win_size=5, sigma_range=None, sigma_spatial=1,
similarity). A larger value results in averaging of pixels with larger
radiometric differences. Note, that the image will be converted using
the `img_as_float` function and thus the standard deviation is in
respect to the range ``[0, 1]``. If the value is ``None`` the standard
respect to the range ``[0, 1]``. If the value is ``None`` the standard
deviation of the ``image`` will be used.
sigma_spatial : float
Standard deviation for range distance. A larger value results in
@@ -116,7 +116,7 @@ def denoise_tv_bregman(image, weight, max_iter=100, eps=1e-3, isotropic=True):
return _denoise_tv_bregman(image, weight, max_iter, eps, isotropic)
def _denoise_tv_chambolle_3d(im, weight=100, eps=2.e-4, n_iter_max=200):
def _denoise_tv_chambolle_3d(im, weight=0.2, eps=2.e-4, n_iter_max=200):
"""Perform total-variation denoising on 3D images.
Parameters
@@ -189,7 +189,7 @@ def _denoise_tv_chambolle_3d(im, weight=100, eps=2.e-4, n_iter_max=200):
return out
def _denoise_tv_chambolle_2d(im, weight=50, eps=2.e-4, n_iter_max=200):
def _denoise_tv_chambolle_2d(im, weight=0.2, eps=2.e-4, n_iter_max=200):
"""Perform total-variation denoising on 2D images.
Parameters
@@ -265,7 +265,7 @@ def _denoise_tv_chambolle_2d(im, weight=50, eps=2.e-4, n_iter_max=200):
return out
def denoise_tv_chambolle(im, weight=50, eps=2.e-4, n_iter_max=200,
def denoise_tv_chambolle(im, weight=0.2, eps=2.e-4, n_iter_max=200,
multichannel=False):
"""Perform total-variation denoising on 2D and 3D images.
skimage/restoration/tests/test_denoise.py
+6 -6
View File
@@ -21,7 +21,7 @@ def test_denoise_tv_chambolle_2d():
# clip noise so that it does not exceed allowed range for float images.
img = np.clip(img, 0, 1)
# denoise
denoised_astro = restoration.denoise_tv_chambolle(img, weight=60.0)
denoised_astro = restoration.denoise_tv_chambolle(img, weight=0.25)
# which dtype?
assert denoised_astro.dtype in [np.float, np.float32, np.float64]
from scipy import ndimage as ndi
@@ -30,12 +30,12 @@ def test_denoise_tv_chambolle_2d():
# test if the total variation has decreased
assert grad_denoised.dtype == np.float
assert (np.sqrt((grad_denoised**2).sum())
< np.sqrt((grad**2).sum()) / 2)
< np.sqrt((grad**2).sum()))
def test_denoise_tv_chambolle_multichannel():
denoised0 = restoration.denoise_tv_chambolle(astro[..., 0], weight=60.0)
denoised = restoration.denoise_tv_chambolle(astro, weight=60.0,
denoised0 = restoration.denoise_tv_chambolle(astro[..., 0], weight=0.25)
denoised = restoration.denoise_tv_chambolle(astro, weight=0.25,
multichannel=True)
assert_equal(denoised[..., 0], denoised0)
@@ -46,7 +46,7 @@ def test_denoise_tv_chambolle_float_result_range():
int_astro = np.multiply(img, 255).astype(np.uint8)
assert np.max(int_astro) > 1
denoised_int_astro = restoration.denoise_tv_chambolle(int_astro,
weight=60.0)
weight=0.25)
# test if the value range of output float data is within [0.0:1.0]
assert denoised_int_astro.dtype == np.float
assert np.max(denoised_int_astro) <= 1.0
@@ -62,7 +62,7 @@ def test_denoise_tv_chambolle_3d():
mask += 20 * np.random.rand(*mask.shape)
mask[mask < 0] = 0
mask[mask > 255] = 255
res = restoration.denoise_tv_chambolle(mask.astype(np.uint8), weight=100)
res = restoration.denoise_tv_chambolle(mask.astype(np.uint8), weight=0.4)
assert res.dtype == np.float
assert res.std() * 255 < mask.std()