diff --git a/skimage/filter/rank/bilateral_rank.pyx b/skimage/filter/rank/bilateral_rank.pyx
index 818f0c64..1a528143 100644
--- a/skimage/filter/rank/bilateral_rank.pyx
+++ b/skimage/filter/rank/bilateral_rank.pyx
@@ -1,11 +1,11 @@
-"""Approximate bilateral rankfilter for local (custom kernel) mean.
+"""Approximate bilateral rank filter for local (custom kernel) mean.
 
 The local histogram is computed using a sliding window similar to the method
 described in:
 
-Reference: Huang, T. ,Yang, G. ;  Tang, G.. "A fast two-dimensional median
-filtering algorithm", IEEE Transactions on Acoustics, Speech and Signal
-Processing, Feb 1979. Volume: 27 , Issue: 1, Page(s): 13 - 18.
+.. [1] Reference: Huang, T. ,Yang, G. ;  Tang, G.. "A fast two-dimensional
+       median filtering algorithm", IEEE Transactions on Acoustics, Speech and
+       Signal Processing, Feb 1979. Volume: 27 , Issue: 1, Page(s): 13 - 18.
 
 Input image can be 8-bit or 16-bit with a value < 4096 (i.e. 12 bit), 8-bit
 images are casted in 16-bit the number of histogram bins is determined from the
diff --git a/skimage/filter/rank/percentile_rank.pyx b/skimage/filter/rank/percentile_rank.pyx
index 1c194f4b..5ad94af4 100644
--- a/skimage/filter/rank/percentile_rank.pyx
+++ b/skimage/filter/rank/percentile_rank.pyx
@@ -1,15 +1,15 @@
 """Inferior and superior ranks, provided by the user, are passed to the kernel
 function to provide a softer version of the rank filters. E.g.
 percentile_autolevel will stretch image levels between percentile [p0, p1]
-instead of using [min,max]. It means that isolate bright or dark pixels will not
-produce halos.
+instead of using [min, max]. It means that isolated bright or dark pixels will
+not produce halos.
 
 The local histogram is computed using a sliding window similar to the method
 described in:
 
-Reference: Huang, T. ,Yang, G. ;  Tang, G.. "A fast two-dimensional median
-filtering algorithm", IEEE Transactions on Acoustics, Speech and Signal
-Processing, Feb 1979. Volume: 27 , Issue: 1, Page(s): 13 - 18.
+.. [1] Reference: Huang, T. ,Yang, G. ;  Tang, G.. "A fast two-dimensional
+       median filtering algorithm", IEEE Transactions on Acoustics, Speech and
+       Signal Processing, Feb 1979. Volume: 27 , Issue: 1, Page(s): 13 - 18.
 
 Input image can be 8-bit or 16-bit with a value < 4096 (i.e. 12 bit), for 16-bit
 input images, the number of histogram bins is determined from the maximum value
diff --git a/skimage/filter/rank/rank.pyx b/skimage/filter/rank/rank.pyx
index c1878f34..3ce2c223 100644
--- a/skimage/filter/rank/rank.pyx
+++ b/skimage/filter/rank/rank.pyx
@@ -1,9 +1,9 @@
 """The local histogram is computed using a sliding window similar to the method
 described in:
 
-Reference: Huang, T. ,Yang, G. ;  Tang, G.. "A fast two-dimensional median
-filtering algorithm", IEEE Transactions on Acoustics, Speech and Signal
-Processing, Feb 1979. Volume: 27 , Issue: 1, Page(s): 13 - 18.
+.. [1] Reference: Huang, T. ,Yang, G. ;  Tang, G.. "A fast two-dimensional
+       median filtering algorithm", IEEE Transactions on Acoustics, Speech and
+       Signal Processing, Feb 1979. Volume: 27 , Issue: 1, Page(s): 13 - 18.
 
 Input image can be 8-bit or 16-bit with a value < 4096 (i.e. 12 bit), for 16-bit
 input images, the number of histogram bins is determined from the maximum value