diff --git a/doc/examples/plot_watershed.py b/doc/examples/plot_watershed.py
index 0fea79f2..7927cb90 100644
--- a/doc/examples/plot_watershed.py
+++ b/doc/examples/plot_watershed.py
@@ -3,23 +3,25 @@
 Watershed segmentation
 ======================
 
-The watershed is a classical algorithm used for **segmentation**, that is, for 
-separating different objects in an image.
+The watershed is a classical algorithm used for **segmentation**, that
+is, for separating different objects in an image.
 
-Starting from user-defined markers, the watershed algorithm treats pixels
-values as a local topography (elevation). The algorithm floods basins from the
-markers, until basins attributed to different markers meet on watershed lines.
-In many cases, markers are chosen as local minima of the image, from which
-basins are flooded.
+Starting from user-defined markers, the watershed algorithm treats
+pixels values as a local topography (elevation). The algorithm floods
+basins from the markers, until basins attributed to different markers
+meet on watershed lines.  In many cases, markers are chosen as local
+minima of the image, from which basins are flooded.
 
-In the example below, two overlapping circles are to be separated. To do so,
-one computes an image that is the distance to the background. The maxima of
-this distance (i.e., the minima of the opposite of the distance) are chosen as
-markers, and the flooding of basins from such markers separates the two circles
-along a watershed line.
+In the example below, two overlapping circles are to be separated. To
+do so, one computes an image that is the distance to the
+background. The maxima of this distance (i.e., the minima of the
+opposite of the distance) are chosen as markers, and the flooding of
+basins from such markers separates the two circles along a watershed
+line.
 
-See http://en.wikipedia.org/wiki/Watershed_(image_processing) for more details
-on the algorithm.
+See `Wikipedia
+<http://en.wikipedia.org/wiki/Watershed_(image_processing)>`__ for
+more details on the algorithm.
 """
 
 import numpy as np