diff --git a/skimage/measure/_sum_blocks.py b/skimage/measure/_sum_blocks.py
index e6a478e5..b349f3e6 100644
--- a/skimage/measure/_sum_blocks.py
+++ b/skimage/measure/_sum_blocks.py
@@ -5,6 +5,12 @@ def sum_blocks(array, factors):
 	"""Sums the elements in blocks of integer factors and pads the original
 	array with zeroes if the dimensions are not perfectly divisible by factors.
 
+    This function is different from resize and rescale in transform._warps in
+    the sense that they use interpolation to upsample or downsample on a 2D
+    array, while this function performs only dawnsampling but on any
+    n-dimensional array and returns the sum of elements in a block of size
+    factors in the original array.
+
     Parameters
     ----------
     array : ndarray
diff --git a/skimage/transform/_warps.py b/skimage/transform/_warps.py
index cca5d1d9..487ed760 100644
--- a/skimage/transform/_warps.py
+++ b/skimage/transform/_warps.py
@@ -8,6 +8,12 @@ from skimage.util.shape import view_as_blocks, _pad_asymmetric_zeros
 def resize(image, output_shape, order=1, mode='constant', cval=0.):
     """Resize image to match a certain size.
 
+    Resize performs interpolation to upsample or downsample 2D arrays. For
+    downsampling any n-dimensional array by performing arithmetic sum or
+    arithmetic mean, see meassure._sum_blocks.sum_blocks and
+    transform._warps.downscale_local_means respectively.
+
+
     Parameters
     ----------
     image : ndarray
@@ -89,6 +95,11 @@ def resize(image, output_shape, order=1, mode='constant', cval=0.):
 def rescale(image, scale, order=1, mode='constant', cval=0.):
     """Scale image by a certain factor.
 
+    Rescale performs interpolation to upsample or downsample 2D arrays. For
+    downsampling any n-dimensional array by performing arithmetic sum or
+    arithmetic mean, see meassure._sum_blocks.sum_blocks and
+    transform._warps.downscale_local_means respectively.
+
     Parameters
     ----------
     image : ndarray
@@ -339,6 +350,12 @@ def downscale_local_means(array, factors):
     the original array with zeroes if the dimensions are not perfectly
     divisible by factors and replaces it with mean i.e. average value.
 
+    This function is different from resize and rescale in the sense that they
+    use interpolation to upsample or downsample on a 2D array, while this
+    function performs only dawnsampling but on any n-dimensional array and
+    returns the arithmetic mean of elements in a block of size factors in the
+    original array.
+
     Parameters
     ----------
     array : ndarray