diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
index 14866cc1012c..ac5706ae7cf7 100644
--- a/lib/matplotlib/image.py
+++ b/lib/matplotlib/image.py
@@ -474,8 +474,10 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
# do not run the vmin/vmax through the same pipeline we can
# have values close or equal to the boundaries end up on the
# wrong side.
- vrange = np.array([self.norm.vmin, self.norm.vmax],
- dtype=scaled_dtype)
+ vmin, vmax = self.norm.vmin, self.norm.vmax
+ if vmin is np.ma.masked:
+ vmin, vmax = a_min, a_max
+ vrange = np.array([vmin, vmax], dtype=scaled_dtype)
A_scaled -= a_min
vrange -= a_min
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
index 87e3c121d4c0..6ffb2e2d0554 100644
--- a/lib/matplotlib/tests/test_image.py
+++ b/lib/matplotlib/tests/test_image.py
@@ -846,6 +846,14 @@ def test_mask_image():
ax2.imshow(A, interpolation='nearest')
+def test_mask_image_all():
+ # Test behavior with an image that is entirely masked does not warn
+ data = np.full((2, 2), np.nan)
+ fig, ax = plt.subplots()
+ ax.imshow(data)
+ fig.canvas.draw_idle() # would emit a warning
+
+
@image_comparison(['imshow_endianess.png'], remove_text=True)
def test_imshow_endianess():
x = np.arange(10)
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