diff --git a/skimage/filters/rank/README.rst b/skimage/filters/rank/README.rst
index 2d6bfb25..6e063ec2 100644
--- a/skimage/filters/rank/README.rst
+++ b/skimage/filters/rank/README.rst
@@ -26,7 +26,7 @@ update the local histogram. The histogram size is 8-bit (256 bins) for 8-bit
 images and 2 to 16-bit for 16-bit images depending on the maximum value of the
 image.
 
-The filter is applied up to the image border, the neighboorhood used is
+The filter is applied up to the image border, the neighborhood used is
 adjusted accordingly. The user may provide a mask image (same size as input
 image) where non zero values are the part of the image participating in the
 histogram computation. By default the entire image is filtered.
diff --git a/skimage/filters/rank/tests/test_rank.py b/skimage/filters/rank/tests/test_rank.py
index 0fda186c..78a97e56 100644
--- a/skimage/filters/rank/tests/test_rank.py
+++ b/skimage/filters/rank/tests/test_rank.py
@@ -87,7 +87,6 @@ def check_all():
 def test_random_sizes():
     # make sure the size is not a problem
 
-    niter = 10
     elem = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]], dtype=np.uint8)
     for m, n in np.random.random_integers(1, 100, size=(10, 2)):
         mask = np.ones((m, n), dtype=np.uint8)