Fixed database typo and removed unnecessary class identifier.
This commit is contained in:
parent
00ad49a143
commit
45fb349a7d
5098 changed files with 952558 additions and 85 deletions
164
venv/Lib/site-packages/skimage/restoration/non_local_means.py
Normal file
164
venv/Lib/site-packages/skimage/restoration/non_local_means.py
Normal file
|
|
@ -0,0 +1,164 @@
|
|||
import numpy as np
|
||||
from warnings import warn
|
||||
from .._shared.utils import convert_to_float
|
||||
from ._nl_means_denoising import (
|
||||
_nl_means_denoising_2d,
|
||||
_nl_means_denoising_3d,
|
||||
_fast_nl_means_denoising_2d,
|
||||
_fast_nl_means_denoising_3d)
|
||||
|
||||
|
||||
def denoise_nl_means(image, patch_size=7, patch_distance=11, h=0.1,
|
||||
multichannel=False, fast_mode=True, sigma=0., *,
|
||||
preserve_range=None):
|
||||
"""Perform non-local means denoising on 2-D or 3-D grayscale images, and
|
||||
2-D RGB images.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
image : 2D or 3D ndarray
|
||||
Input image to be denoised, which can be 2D or 3D, and grayscale
|
||||
or RGB (for 2D images only, see ``multichannel`` parameter).
|
||||
patch_size : int, optional
|
||||
Size of patches used for denoising.
|
||||
patch_distance : int, optional
|
||||
Maximal distance in pixels where to search patches used for denoising.
|
||||
h : float, optional
|
||||
Cut-off distance (in gray levels). The higher h, the more permissive
|
||||
one is in accepting patches. A higher h results in a smoother image,
|
||||
at the expense of blurring features. For a Gaussian noise of standard
|
||||
deviation sigma, a rule of thumb is to choose the value of h to be
|
||||
sigma of slightly less.
|
||||
multichannel : bool, optional
|
||||
Whether the last axis of the image is to be interpreted as multiple
|
||||
channels or another spatial dimension.
|
||||
fast_mode : bool, optional
|
||||
If True (default value), a fast version of the non-local means
|
||||
algorithm is used. If False, the original version of non-local means is
|
||||
used. See the Notes section for more details about the algorithms.
|
||||
sigma : float, optional
|
||||
The standard deviation of the (Gaussian) noise. If provided, a more
|
||||
robust computation of patch weights is computed that takes the expected
|
||||
noise variance into account (see Notes below).
|
||||
preserve_range : bool, optional
|
||||
Whether to keep the original range of values. Otherwise, the input
|
||||
image is converted according to the conventions of `img_as_float`.
|
||||
Also see https://scikit-image.org/docs/dev/user_guide/data_types.html
|
||||
|
||||
Returns
|
||||
-------
|
||||
result : ndarray
|
||||
Denoised image, of same shape as `image`.
|
||||
|
||||
Notes
|
||||
-----
|
||||
|
||||
The non-local means algorithm is well suited for denoising images with
|
||||
specific textures. The principle of the algorithm is to average the value
|
||||
of a given pixel with values of other pixels in a limited neighbourhood,
|
||||
provided that the *patches* centered on the other pixels are similar enough
|
||||
to the patch centered on the pixel of interest.
|
||||
|
||||
In the original version of the algorithm [1]_, corresponding to
|
||||
``fast=False``, the computational complexity is::
|
||||
|
||||
image.size * patch_size ** image.ndim * patch_distance ** image.ndim
|
||||
|
||||
Hence, changing the size of patches or their maximal distance has a
|
||||
strong effect on computing times, especially for 3-D images.
|
||||
|
||||
However, the default behavior corresponds to ``fast_mode=True``, for which
|
||||
another version of non-local means [2]_ is used, corresponding to a
|
||||
complexity of::
|
||||
|
||||
image.size * patch_distance ** image.ndim
|
||||
|
||||
The computing time depends only weakly on the patch size, thanks to
|
||||
the computation of the integral of patches distances for a given
|
||||
shift, that reduces the number of operations [1]_. Therefore, this
|
||||
algorithm executes faster than the classic algorithm
|
||||
(``fast_mode=False``), at the expense of using twice as much memory.
|
||||
This implementation has been proven to be more efficient compared to
|
||||
other alternatives, see e.g. [3]_.
|
||||
|
||||
Compared to the classic algorithm, all pixels of a patch contribute
|
||||
to the distance to another patch with the same weight, no matter
|
||||
their distance to the center of the patch. This coarser computation
|
||||
of the distance can result in a slightly poorer denoising
|
||||
performance. Moreover, for small images (images with a linear size
|
||||
that is only a few times the patch size), the classic algorithm can
|
||||
be faster due to boundary effects.
|
||||
|
||||
The image is padded using the `reflect` mode of `skimage.util.pad`
|
||||
before denoising.
|
||||
|
||||
If the noise standard deviation, `sigma`, is provided a more robust
|
||||
computation of patch weights is used. Subtracting the known noise variance
|
||||
from the computed patch distances improves the estimates of patch
|
||||
similarity, giving a moderate improvement to denoising performance [4]_.
|
||||
It was also mentioned as an option for the fast variant of the algorithm in
|
||||
[3]_.
|
||||
|
||||
When `sigma` is provided, a smaller `h` should typically be used to
|
||||
avoid oversmoothing. The optimal value for `h` depends on the image
|
||||
content and noise level, but a reasonable starting point is
|
||||
``h = 0.8 * sigma`` when `fast_mode` is `True`, or ``h = 0.6 * sigma`` when
|
||||
`fast_mode` is `False`.
|
||||
|
||||
References
|
||||
----------
|
||||
.. [1] A. Buades, B. Coll, & J-M. Morel. A non-local algorithm for image
|
||||
denoising. In CVPR 2005, Vol. 2, pp. 60-65, IEEE.
|
||||
:DOI:`10.1109/CVPR.2005.38`
|
||||
|
||||
.. [2] J. Darbon, A. Cunha, T.F. Chan, S. Osher, and G.J. Jensen, Fast
|
||||
nonlocal filtering applied to electron cryomicroscopy, in 5th IEEE
|
||||
International Symposium on Biomedical Imaging: From Nano to Macro,
|
||||
2008, pp. 1331-1334.
|
||||
:DOI:`10.1109/ISBI.2008.4541250`
|
||||
|
||||
.. [3] Jacques Froment. Parameter-Free Fast Pixelwise Non-Local Means
|
||||
Denoising. Image Processing On Line, 2014, vol. 4, pp. 300-326.
|
||||
:DOI:`10.5201/ipol.2014.120`
|
||||
|
||||
.. [4] A. Buades, B. Coll, & J-M. Morel. Non-Local Means Denoising.
|
||||
Image Processing On Line, 2011, vol. 1, pp. 208-212.
|
||||
:DOI:`10.5201/ipol.2011.bcm_nlm`
|
||||
|
||||
Examples
|
||||
--------
|
||||
>>> a = np.zeros((40, 40))
|
||||
>>> a[10:-10, 10:-10] = 1.
|
||||
>>> a += 0.3 * np.random.randn(*a.shape)
|
||||
>>> denoised_a = denoise_nl_means(a, 7, 5, 0.1)
|
||||
|
||||
"""
|
||||
if image.ndim == 2:
|
||||
image = image[..., np.newaxis]
|
||||
multichannel = True
|
||||
if image.ndim != 3:
|
||||
raise NotImplementedError("Non-local means denoising is only \
|
||||
implemented for 2D grayscale and RGB images or 3-D grayscale images.")
|
||||
|
||||
if preserve_range is None and np.issubdtype(image.dtype, np.integer):
|
||||
warn('Image dtype is not float. By default denoise_nl_means will '
|
||||
'assume you want to preserve the range of your image '
|
||||
'(preserve_range=True). In scikit-image 0.19 this behavior will '
|
||||
'change to preserve_range=False. To avoid this warning, '
|
||||
'explicitly specify the preserve_range parameter.',
|
||||
stacklevel=2)
|
||||
preserve_range = True
|
||||
|
||||
image = convert_to_float(image, preserve_range)
|
||||
|
||||
kwargs = dict(s=patch_size, d=patch_distance, h=h, var=sigma * sigma)
|
||||
if multichannel: # 2-D images
|
||||
if fast_mode:
|
||||
return _fast_nl_means_denoising_2d(image, **kwargs)
|
||||
else:
|
||||
return _nl_means_denoising_2d(image, **kwargs)
|
||||
else: # 3-D grayscale
|
||||
if fast_mode:
|
||||
return _fast_nl_means_denoising_3d(image, **kwargs)
|
||||
else:
|
||||
return _nl_means_denoising_3d(image, **kwargs)
|
||||
Loading…
Add table
Add a link
Reference in a new issue