diff --git a/normalizing_flows/bijections/finite/multiscale/architectures.py b/normalizing_flows/bijections/finite/multiscale/architectures.py
index 5ecff68..21f7d8f 100644
--- a/normalizing_flows/bijections/finite/multiscale/architectures.py
+++ b/normalizing_flows/bijections/finite/multiscale/architectures.py
@@ -13,14 +13,25 @@ def make_image_layers(event_shape,
     if len(event_shape) != 3:
         raise ValueError("Multichannel image transformation are only possible for inputs with three axes.")
 
+    assert n_layers >= 1
+
     bijections = [ElementwiseAffine(event_shape=event_shape)]
-    for _ in range(n_layers):
+    for _ in range(n_layers - 1):
         bijections.append(
             MultiscaleBijection(
                 input_event_shape=bijections[-1].transformed_shape,
                 transformer_class=transformer_class
             )
         )
+    bijections.append(
+        MultiscaleBijection(
+            input_event_shape=bijections[-1].transformed_shape,
+            transformer_class=transformer_class,
+            n_checkerboard_layers=4,
+            squeeze_layer=False,
+            n_channel_wise_layers=0
+        )
+    )
     bijections.append(ElementwiseAffine(event_shape=bijections[-1].transformed_shape))
     return bijections
 
@@ -35,4 +46,3 @@ def __init__(self,
         bijections = make_image_layers(event_shape, Affine, n_layers)
         super().__init__(event_shape, bijections, **kwargs)
         self.transformed_shape = bijections[-1].transformed_shape
-