diff --git a/saqc/funcs/outliers.py b/saqc/funcs/outliers.py
index ff6f629a7f0685e30db7c1643cba8e4c7c8c9d87..2a5652ce6920dd5773cde2337d231e586518ccfd 100644
--- a/saqc/funcs/outliers.py
+++ b/saqc/funcs/outliers.py
@@ -179,8 +179,8 @@ class OutliersMixin:
         p: int = 1,
         density: Literal["auto"] | float = "auto",
         fill_na: bool = True,
-        slope_correct=True,
-        min_offset=None,
+        slope_correct: bool = True,
+        min_offset: float = None,
         flag: float = BAD,
         **kwargs,
     ) -> "SaQC":
@@ -249,6 +249,15 @@ class OutliersMixin:
         fill_na :
             If True, NaNs in the data are filled with a linear interpolation.
 
+        slope_correct :
+            if True, a correction is applied, that removes outlier cluster that actually
+            just seem to be steep slopes
+
+        min_offset :
+            If set, only those outlier cluster will be flagged, that are preceeded and succeeeded
+            by sufficiently large value "jumps". Defaults to estimating the sufficient value jumps from
+            the median over the absolute step sizes between data points.
+
         See Also
         --------
         :ref:`introduction to outlier detection with
@@ -374,7 +383,7 @@ class OutliersMixin:
             g_mask = s_mask.diff()
             g_mask = g_mask.cumsum()
             dat = self._data[field]
-            od_groups = dat.groupby(by=g_mask)
+            od_groups = dat.interpolate('linear').groupby(by=g_mask)
             first_vals = od_groups.first()
             last_vals = od_groups.last()
             max_vals = od_groups.max()
@@ -385,7 +394,9 @@ class OutliersMixin:
                     eps = d_diff.abs().median()
                     if eps == 0:
                         eps = d_diff[d_diff != 0].abs().median()
-                    eps = 3 * eps
+                else:
+                    eps = density
+                eps = 3 * eps
             else:
                 eps = min_offset
             up_slopes = (min_vals + eps >= last_vals.shift(1)) & (