skan.pre: Image preprocessing#

skan.pre.hyperball(ndim, radius)[source]#

Return a binary morphological filter containing pixels within radius.

Parameters:

  • ndim (int) – The number of dimensions of the filter.

  • radius (int) – The radius of the filter.

Returns:

ball – The required structural element

Return type:

array of bool, shape [2 * radius + 1,] * ndim

skan.pre.threshold(image, *, sigma=0.0, radius=0, offset=0.0, method='sauvola', smooth_method='Gaussian')[source]#

Use scikit-image filters to “intelligently” threshold an image.

Parameters:

  • image (array, shape (M, N, ...[, 3])) – Input image, conformant with scikit-image data type specification [1].

  • sigma (float, optional) – If positive, use Gaussian filtering to smooth the image before thresholding.

  • radius (int, optional) – If given, use local median thresholding instead of global.

  • offset (float, optional) – If given, reduce the threshold by this amount. Higher values result in fewer pixels above the threshold.

  • method ({'sauvola', 'niblack', 'median'}) – Which method to use for thresholding. Sauvola is 100x faster, but median might be more accurate.

  • smooth_method ({'Gaussian', 'TV'}) – Which method to use for smoothing. Choose from Gaussian smoothing and total variation denoising.

Returns:

thresholded – The thresholded image.

Return type:

image of bool, same shape as image

References