wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-08-02 13:03:48 +08:00
Code Issues Packages Projects Releases Wiki Activity

behaviour for 16 bit images matches behaviour for 8 bit images.

Browse Source
This commit is contained in:
walter
2016-06-06 17:12:57 +02:00
parent 6378bc1c39
commit 02b21fdfe3
1 changed files with 23 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/feature/texture.py
+23 -15
View File
@@ -13,16 +13,15 @@ from ._texture import (_glcm_loop,
def greycomatrix(image, distances, angles, levels=None, symmetric=False,
normed=False):
"""Calculate the grey-level co-occurrence matrix.
""" *** YOYO *** Calculate the grey-level co-occurrence matrix.
A grey level co-occurrence matrix is a histogram of co-occurring
greyscale values at a given offset over an image.
Parameters
----------
image : array_like of uint8
Integer typed input image. The image will be cast to uint8, so
the maximum value must be less than 256.
image : array_like of uint8 or uint16.
Integer typed input image. The image will be cast to uint16.
distances : array_like
List of pixel pair distance offsets.
angles : array_like
@@ -30,10 +29,8 @@ def greycomatrix(image, distances, angles, levels=None, symmetric=False,
levels : int, optional
The input image should contain integers in [0, levels-1],
where levels indicate the number of grey-levels counted
(typically 256 for an 8-bit image). Be aware that the co-occurrence
matrix for every angle and every distance is of size levels x levels.
Choosing a too large level might result in exceedingly large matrix.
If you have 16 bit or 32 bit images, consider binning.
(typically 256 for an 8-bit image). This argument is required for
16-bit images and is typically the maximum of the image.
symmetric : bool, optional
If True, the output matrix `P[:, :, d, theta]` is symmetric. This
is accomplished by ignoring the order of value pairs, so both
@@ -52,7 +49,8 @@ def greycomatrix(image, distances, angles, levels=None, symmetric=False,
`P[i,j,d,theta]` is the number of times that grey-level `j`
occurs at a distance `d` and at an angle `theta` from
grey-level `i`. If `normed` is `False`, the output is of
type uint32, otherwise it is float64.
type uint32, otherwise it is float64. The dimensions are:
levels x levels x number of distances x number of angles.
References
----------
@@ -103,15 +101,25 @@ def greycomatrix(image, distances, angles, levels=None, symmetric=False,
assert image.min() >= 0
image_max = image.max()
if levels is None:
# if levels is not given, we assume that there are [0, image_max -1] levels to
# be considered. There would be only zeros for all other rows and columns.
levels = image_max + 1
#if image.dtype in [np.float, np.float16, np.float32, np.float]
if image.dtype == np.float:
raise ValueError("Float images are not supported by greycomatrix."
"The image needs to be casted to uint8 or uint16.")
# for 16 bit images, levels must be set.
if image.dtype != np.uint8:
if levels is None:
raise ValueError("For images other than 8 bit images, argument levels must be set to a user defined value."
"A large value will produce a large output matrix, potentially causing memory problems."
"In this case, one might consider binning the image prior to calling greycomatrix.")
if levels is None:
levels = 256
assert image_max < levels
# we cast to uint16 (because of fixed typing in cython)
# this has no impact on the size of the co-occurrence matrix.
# image is cast to uint16 (because of fixed typing in cython)
image = image.astype(np.uint16)
distances = np.ascontiguousarray(distances, dtype=np.float64)