diff --git a/src/depiction/calibration/methods/calibration_method_constant_global_shift.py b/src/depiction/calibration/methods/calibration_method_constant_global_shift.py
index 27af4f0..414bb81 100644
--- a/src/depiction/calibration/methods/calibration_method_constant_global_shift.py
+++ b/src/depiction/calibration/methods/calibration_method_constant_global_shift.py
@@ -1,4 +1,5 @@
 import numpy as np
+import xarray
 from numpy.typing import NDArray
 from xarray import DataArray
 
@@ -30,16 +31,12 @@ def extract_spectrum_features(self, peak_mz_arr: NDArray[float], peak_int_arr: N
 
     def preprocess_image_features(self, all_features: MultiChannelImage) -> MultiChannelImage:
         # we compute the actual global distance here
-        global_distance = np.nanmedian(all_features.data_flat.ravel())
-        # create one copy per spectrum
-        n_spectra = all_features.n_nonzero
+        global_distance = np.nanmedian(all_features.data_flat.data.ravel())
+        # return one value per spectrum
         return MultiChannelImage(
-            data=DataArray(
-                np.full((n_spectra, 1, 1), global_distance), dims=["y", "x", "c"], coords=all_features.coordinates_flat
-            ),
-            is_foreground=DataArray(
-                np.ones((n_spectra, 1), dtype=bool), dims=["y", "x"], coords=all_features.coordinates_flat
-            ),
+            data=xarray.full_like(all_features.data_spatial.isel(c=[0]), global_distance),
+            is_foreground=all_features.fg_mask,
+            is_foreground_label=all_features.is_foreground_label,
         )
 
     def fit_spectrum_model(self, features: DataArray) -> DataArray: