diff --git a/skimage/segmentation/random_walker_segmentation.py b/skimage/segmentation/random_walker_segmentation.py
index 6df714d2..3e1c755f 100644
--- a/skimage/segmentation/random_walker_segmentation.py
+++ b/skimage/segmentation/random_walker_segmentation.py
@@ -334,17 +334,18 @@ def random_walker(data, labels, beta=130, mode='bf', tol=1.e-3, copy=True,
     # Parse input data
     if not multichannel:
         # We work with 4-D arrays of floats
+        assert data.ndim > 1 and data.ndim < 4, 'For non-multichannel input, \
+                                                 data must be of dimension 2 \
+                                                 or 3.'
         dims = data.shape
-        data = np.atleast_3d(img_as_float(data))
-        data.shape += (1,)
+        data = np.atleast_3d(img_as_float(data.copy()))[..., np.newaxis]
     else:
         dims = data[..., 0].shape
         assert multichannel and data.ndim > 2, 'For multichannel input, data \
                                                 must have >= 3 dimensions.'
-        data = img_as_float(data)
+        data = img_as_float(data.copy())
         if data.ndim == 3:
-            data.shape += (1,)
-            data = data.transpose((0, 1, 3, 2))
+            data = data[..., np.newaxis].transpose((0, 1, 3, 2))
 
     if copy:
         labels = np.copy(labels)