diameter_opening(image, diameter_threshold=8, connectivity=1, parent=None, tree_traverser=None)
Diameter opening removes all bright structures of an image with maximal extension smaller than diameter_threshold. The maximal extension is defined as the maximal extension of the bounding box. The operator is also called Bounding Box Opening. In practice, the result is similar to a morphological opening, but long and thin structures are not removed.
Technically, this operator is based on the max-tree representation of the image.
The input image for which the area_opening is to be calculated. This image can be of any type.
The maximal extension parameter (number of pixels). The default value is 8.
The neighborhood connectivity. The integer represents the maximum number of orthogonal steps to reach a neighbor. In 2D, it is 1 for a 4-neighborhood and 2 for a 8-neighborhood. Default value is 1.
Parent image representing the max tree of the image. The value of each pixel is the index of its parent in the ravelled array.
The ordered pixel indices (referring to the ravelled array). The pixels are ordered such that every pixel is preceded by its parent (except for the root which has no parent).
Output image of the same shape and type as the input image.
Perform a diameter opening of the image.
We create an image (quadratic function with a maximum in the center and 4 additional local maxima.
This example is valid syntax, but we were not able to check execution>>> w = 12
... x, y = np.mgrid[0:w,0:w]
... f = 20 - 0.2*((x - w/2)**2 + (y-w/2)**2)
... f[2:3,1:5] = 40; f[2:4,9:11] = 60; f[9:11,2:4] = 80
... f[9:10,9:11] = 100; f[10,10] = 100
... f = f.astype(np.int)
We can calculate the diameter opening:
This example is valid syntax, but we were not able to check execution>>> open = diameter_opening(f, 3, connectivity=1)
The peaks with a maximal extension of 2 or less are removed. The remaining peaks have all a maximal extension of at least 3.
See :The following pages refer to to this document either explicitly or contain code examples using this.
skimage.morphology.max_tree.diameter_opening
skimage.morphology.max_tree.area_closing
skimage.morphology.max_tree.area_opening
skimage.morphology.max_tree.diameter_closing
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