subtract_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=False)
Subtracting the mean value may introduce underflow. To compensate this potential underflow, the obtained difference is downscaled by a factor of 2 and shifted by :None:None:`n_bins / 2 - 1`, the median value of the local histogram (:None:None:`n_bins = max(3, image.max()) +1` for 16-bits images and 256 otherwise).
Input image.
The neighborhood expressed as a 2-D array of 1's and 0's.
If None, a new array is allocated.
Mask array that defines (>0) area of the image included in the local neighborhood. If None, the complete image is used (default).
Offset added to the structuring element center point. Shift is bounded to the structuring element sizes (center must be inside the given structuring element).
Output image.
Return image subtracted from its local mean.
>>> from skimage import dataSee :
... from skimage.morphology import disk
... from skimage.filters.rank import subtract_mean
... img = data.camera()
... out = subtract_mean(img, disk(5))
The following pages refer to to this document either explicitly or contain code examples using this.
skimage.filters.rank.generic.subtract_mean
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