h_maxima(image, h, selem=None)
The local maxima are defined as connected sets of pixels with equal grey level strictly greater than the grey level of all pixels in direct neighborhood of the set.
A local maximum M of height h is a local maximum for which there is at least one path joining M with a higher maximum on which the minimal value is f(M) - h (i.e. the values along the path are not decreasing by more than h with respect to the maximum's value) and no path for which the minimal value is greater.
The input image for which the maxima are to be calculated.
The minimal height of all extracted maxima.
The neighborhood expressed as an n-D array of 1's and 0's. Default is the ball of radius 1 according to the maximum norm (i.e. a 3x3 square for 2D images, a 3x3x3 cube for 3D images, etc.)
The maxima of height >= h. The resulting image is a binary image, where pixels belonging to the selected maxima take value 1, the others take value 0.
Determine all maxima of the image with height >= h.
>>> import numpy as np
... from skimage.morphology import extrema
We create an image (quadratic function with a maximum in the center and 4 additional constant maxima. The heights of the maxima are: 1, 21, 41, 61, 81
This example is valid syntax, but we were not able to check execution>>> w = 10
... x, y = np.mgrid[0:w,0:w]
... f = 20 - 0.2*((x - w/2)**2 + (y-w/2)**2)
... f[2:4,2:4] = 40; f[2:4,7:9] = 60; f[7:9,2:4] = 80; f[7:9,7:9] = 100
... f = f.astype(np.int)
We can calculate all maxima with a height of at least 40:
This example is valid syntax, but we were not able to check execution>>> maxima = extrema.h_maxima(f, 40)
The resulting image will contain 3 local maxima.
See :The following pages refer to to this document either explicitly or contain code examples using this.
skimage.morphology.extrema.local_maxima
skimage.morphology.extrema.h_minima
skimage.morphology.extrema.h_maxima
skimage.morphology.extrema.local_minima
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