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()

skimage/filter/rank/_crank8.pyx

@@ -312,11 +312,7 @@ cdef inline np.uint8_t kernel_otsu(Py_ssize_t * histo, float pop, np.uint8_t g,
                 max_i = i
             q1 = new_q1
 
-    if g > max_i:
-        return <np.uint8_t>255
-    else:
-        return <np.uint8_t>0
-
+    return <np.uint8_t> max_i
 
 
 # -----------------------------------------------------------------

skimage/filter/rank/demo/demo_single.py

@@ -4,27 +4,34 @@ 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 denoise_bilateral
+from skimage.filter import threshold_otsu
 
 if __name__ == '__main__':
-    a8 = data.camera()
-    a16 = data.camera().astype(np.uint16)*4
-
     p8 = data.page()
 
-    selem = disk(20)
+    radius = 10
+    selem = disk(radius)
 
-    otsu = rank.otsu(p8,selem)
+    loc_otsu = rank.otsu(p8,selem)
+    t_glob_otsu = threshold_otsu(p8)
+    glob_otsu = p8>=t_glob_otsu
 
 
     plt.figure()
-    plt.subplot(1,2,1)
-    plt.imshow(p8)
+    plt.subplot(2,2,1)
+    plt.imshow(p8,cmap=plt.cm.gray)
+    plt.xlabel('original')
     plt.colorbar()
-    plt.subplot(1,2,2)
-    plt.imshow(otsu)
+    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()
 
 

skimage/filter/rank/rank.pyx

@@ -715,7 +715,7 @@ def entropy(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
                   mask=mask, shift_x=shift_x, shift_y=shift_y)
 
 def otsu(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
-    """Returns the image threshold using a the Otsu [otsu]_ locally .
+    """Returns the Otsu's threshold value for each pixel.
 
     Parameters
     ----------
@@ -738,7 +738,7 @@ def otsu(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
     Returns
     -------
     out : uint8 array or uint16 array (same as input image)
-        threshold image
+        Otsu's threshold values
 
     References
     ----------
@@ -753,6 +753,7 @@ def otsu(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
     >>> # defining a 8- and a 16-bit test images
     >>> a8 = data.camera()
     >>> loc_otsu = otsu(a8,disk(5))
+    >>> thresh_image = a8 >= loc_otsu
 
     """