"""
=====================
Local Otsu Threshold
=====================
This example shows how Otsu's threshold [1]_ method can be applied locally.
For each pixel, an "optimal" threshold is determined by maximizing the variance between two classes of pixels
of the local neighborhood defined by a structuring element.

The example compares the local threshold with the global threshold.

.. note: local threshold is much slower than global one.

.. [1] http://en.wikipedia.org/wiki/Otsu's_method

"""
import matplotlib.pyplot as plt

from skimage import data
from skimage.morphology.selem import disk
import skimage.filter.rank as rank
from skimage.filter import threshold_otsu


p8 = data.page()

radius = 10
selem = disk(radius)

loc_otsu = rank.otsu(p8,selem)
t_glob_otsu = threshold_otsu(p8)
glob_otsu = p8>=t_glob_otsu


plt.figure()
plt.subplot(2,2,1)
plt.imshow(p8,cmap=plt.cm.gray)
plt.xlabel('original')
plt.colorbar()
plt.subplot(2,2,2)
plt.imshow(loc_otsu,cmap=plt.cm.gray)
plt.xlabel('local Otsu ($radius=%d$)'%radius)
plt.colorbar()
plt.subplot(2,2,3)
plt.imshow(p8>=loc_otsu,cmap=plt.cm.gray)
plt.xlabel('original>=local Otsu'%t_glob_otsu)
plt.subplot(2,2,4)
plt.imshow(glob_otsu,cmap=plt.cm.gray)
plt.xlabel('global Otsu ($t=%d$)'%t_glob_otsu)
plt.show()