noise-filter

noise_filter

skimage.filters.rank.noise_filter(image, selem, out=None, mask=None, shift_x=False, shift_y=False) [source]

Noise feature.

Parameters:

image : 2-D array (uint8, uint16)

Input image.

selem : 2-D array

The neighborhood expressed as a 2-D array of 1’s and 0’s.

out : 2-D array (same dtype as input)

If None, a new array is allocated.

mask : ndarray

Mask array that defines (>0) area of the image included in the local neighborhood. If None, the complete image is used (default).

shift_x, shift_y : int

Offset added to the structuring element center point. Shift is bounded to the structuring element sizes (center must be inside the given structuring element).

Returns:

out : 2-D array (same dtype as input image)

Output image.

References

[R217] N. Hashimoto et al. Referenceless image quality evaluation for whole slide imaging. J Pathol Inform 2012;3:9.

Examples

>>> from skimage import data
>>> from skimage.morphology import disk
>>> from skimage.filters.rank import noise_filter
>>> img = data.camera()
>>> out = noise_filter(img, disk(5))
doc_scikit_image
2017-01-12 17:22:34
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