diff --git a/holoviews/element/raster.py b/holoviews/element/raster.py
index 5c8af06500..8e1fc421d0 100644
--- a/holoviews/element/raster.py
+++ b/holoviews/element/raster.py
@@ -12,7 +12,7 @@
                     Overlay, Element, Dataset, NdElement)
 from ..core.boundingregion import BoundingRegion, BoundingBox
 from ..core.sheetcoords import SheetCoordinateSystem
-from ..core.util import pd
+from ..core.util import pd, max_range
 from .chart import Curve
 from .tabular import Table
 from .util import compute_edges, compute_slice_bounds, categorical_aggregate2d
@@ -76,6 +76,21 @@ def __getitem__(self, slices):
                               extents=None)
 
 
+    def range(self, dim, data_range=True):
+        idx = self.get_dimension_index(dim)
+        if data_range and idx == 2:
+            dimension = self.get_dimension(dim)
+            drange = self.data.min(), self.data.max()
+            drange = max_range([drange, dimension.soft_range])
+            if dimension.range[0] is not None:
+                return (dimension.range[0], drange[1])
+            elif dimension.range[1] is not None:
+                return (drange[0], dimension.range[1])
+            else:
+                return drange
+        return super(Raster, self).range(dim, data_range)
+
+
     def dimension_values(self, dim, expanded=True, flat=True):
         """
         The set of samples available along a particular dimension.
diff --git a/tests/testraster.py b/tests/testraster.py
index f9ad53d26d..819843be7b 100644
--- a/tests/testraster.py
+++ b/tests/testraster.py
@@ -38,3 +38,15 @@ def test_image_sample(self):
         self.assertEqual(image.sample(y=0.25),
                          Curve(np.array([(-0.333333, 0), (0, 1), (0.333333, 2)]),
                                kdims=['x'], vdims=['z']))
+
+    def test_raster_range_masked(self):
+        arr = np.random.rand(10,10)-0.5
+        arr = np.ma.masked_where(arr<=0, arr)
+        rrange = Raster(arr).range(2)
+        self.assertEqual(rrange, (np.min(arr), np.max(arr)))
+
+    def test_image_range_masked(self):
+        arr = np.random.rand(10,10)-0.5
+        arr = np.ma.masked_where(arr<=0, arr)
+        rrange = Image(arr).range(2)
+        self.assertEqual(rrange, (np.min(arr), np.max(arr)))