diff --git a/AUTHORS.md b/AUTHORS.md
index 577927e3d2..a8da9ec5f5 100644
--- a/AUTHORS.md
+++ b/AUTHORS.md
@@ -115,3 +115,4 @@ The following people have made contributions to this project:
 - [Albert Brotzer](https://github.com/albertbrotzer)
 - [Alexandra Melzer](https://github.com/armelzer)
 - [Francesc Lucas Carbó (cesclc)](https://github.com/cesclc)
+- [Göte Kleringer (Grukank)](https://github.com/Grukank)
diff --git a/satpy/enhancements/colormap.py b/satpy/enhancements/colormap.py
index 84f60b58de..d41eda3579 100644
--- a/satpy/enhancements/colormap.py
+++ b/satpy/enhancements/colormap.py
@@ -41,12 +41,16 @@ def lookup(img, **kwargs):
 @on_separate_bands
 @using_map_blocks
 def _lookup_table(band_data, luts=None, index=-1):
+    # Save positions of NaNs
+    nans = np.isfinite(band_data)
     # NaN/null values will become 0
     lut = luts[:, index] if len(luts.shape) == 2 else luts
     band_data = band_data.clip(0, lut.size - 1)
     # Convert to uint8, with NaN/null values changed into 0
     band_data = np.nan_to_num(band_data).astype(np.uint8)
-    return lut[band_data]
+    # Lookup data, but with replaced NaNs from saved positions
+    res = np.where(nans, lut[band_data], np.nan)
+    return res
 
 
 def colorize(img, **kwargs):  # noqa: D417
diff --git a/satpy/tests/enhancement_tests/test_colormap.py b/satpy/tests/enhancement_tests/test_colormap.py
index bff59801a3..e3f99eacb1 100644
--- a/satpy/tests/enhancement_tests/test_colormap.py
+++ b/satpy/tests/enhancement_tests/test_colormap.py
@@ -42,16 +42,16 @@ def test_lookup(self):
         """Test the lookup enhancement function."""
         from satpy.enhancements.colormap import lookup
         expected = np.array([[
-            [0., 0., 0., 0.333333, 0.705882],
+            [np.nan, 0., 0., 0.333333, 0.705882],
             [1., 1., 1., 1., 1.]]])
         lut = np.arange(256.)
         run_and_check_enhancement(lookup, self.ch1, expected, luts=lut)
 
-        expected = np.array([[[0., 0., 0., 0.333333, 0.705882],
+        expected = np.array([[[np.nan, 0., 0., 0.333333, 0.705882],
                               [1., 1., 1., 1., 1.]],
-                             [[0., 0., 0., 0.333333, 0.705882],
+                             [[np.nan, 0., 0., 0.333333, 0.705882],
                               [1., 1., 1., 1., 1.]],
-                             [[0., 0., 0., 0.333333, 0.705882],
+                             [[np.nan, 0., 0., 0.333333, 0.705882],
                               [1., 1., 1., 1., 1.]]])
         lut = np.arange(256.)
         lut = np.vstack((lut, lut, lut)).T