local Otsu returns now the threshold values

doc/examples/applications/plot_rank_filters.py

@@ -308,6 +308,56 @@ plt.imshow(ima[200:350,350:450],cmap=plt.cm.gray)
 plt.subplot(2,2,4)
 plt.imshow(penh[200:350,350:450],cmap=plt.cm.gray)
 
+"""
+.. image:: PLOT2RST.current_figure
+
+Image threshold
+===============
+The Otsu's threshold [1]_ method can be applied locally using local greylevel distribution.
+In the example below, 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 `skimage.filter.threshold_otsu``.
+
+.. note: local threshold is much slower than global one.
+
+.. [1] http://en.wikipedia.org/wiki/Otsu's_method
+
+"""
+from skimage.filter.rank import otsu
+from skimage.filter import threshold_otsu
+
+p8 = data.page()
+
+radius = 10
+selem = disk(radius)
+
+# t_loc_otsu is an image
+t_loc_otsu = otsu(p8,selem)
+loc_otsu = p8>=t_loc_otsu
+
+# t_glob_otsu is a scalar
+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()
+
+
 """
 .. image:: PLOT2RST.current_figure
 

doc/examples/plot_local_otsu.py

@@ -0,0 +1,49 @@
+"""
+=====================
+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()