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

1 2 3 4 5

>>> 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))