diff --git a/pyzebra/ccl_process.py b/pyzebra/ccl_process.py
index 54c1f77..ea032fa 100644
--- a/pyzebra/ccl_process.py
+++ b/pyzebra/ccl_process.py
@@ -68,7 +68,10 @@ def _parameters_match(scan1, scan2):
             if max(r1_start - r2_end, r2_start - r1_end) > max_range_gap:
                 return False
 
-        elif np.max(np.abs(scan1[param] - scan2[param])) > PARAM_PRECISIONS[param]:
+        elif (
+            np.max(np.abs(np.median(scan1[param]) - np.median(scan2[param])))
+            > PARAM_PRECISIONS[param]
+        ):
             return False
 
     return True
@@ -85,7 +88,10 @@ def merge_datasets(dataset_into, dataset_from):
     for scan_into in dataset_into:
         for ind, scan_from in enumerate(dataset_from):
             if _parameters_match(scan_into, scan_from) and not merged[ind]:
-                merge_scans(scan_into, scan_from)
+                if scan_into["counts"].ndim == 3:
+                    merge_h5_scans(scan_into, scan_from)
+                else:  # scan_into["counts"].ndim == 1
+                    merge_scans(scan_into, scan_from)
                 merged[ind] = True
 
     for scan_from in dataset_from:
@@ -147,6 +153,63 @@ def merge_scans(scan_into, scan_from):
     print(f'Merging scans: {scan_into["idx"]} ({fname1}) <-- {scan_from["idx"]} ({fname2})')
 
 
+def merge_h5_scans(scan_into, scan_from):
+    if "init_scan" not in scan_into:
+        scan_into["init_scan"] = scan_into.copy()
+
+    if "merged_scans" not in scan_into:
+        scan_into["merged_scans"] = []
+
+    for scan in scan_into["merged_scans"]:
+        if scan_from is scan:
+            print("Already merged scan")
+            return
+
+    scan_into["merged_scans"].append(scan_from)
+
+    scan_motor = scan_into["scan_motor"]  # the same as scan_from["scan_motor"]
+
+    pos_all = scan_into["init_scan"][scan_motor]
+    val_all = scan_into["init_scan"]["counts"]
+    err_all = scan_into["init_scan"]["counts_err"] ** 2
+    for scan in scan_into["merged_scans"]:
+        pos_all = np.append(pos_all, scan[scan_motor])
+        val_all = np.concatenate((val_all, scan["counts"]))
+        err_all = np.concatenate((err_all, scan["counts_err"] ** 2))
+
+    sort_index = np.argsort(pos_all)
+    pos_all = pos_all[sort_index]
+    val_all = val_all[sort_index]
+    err_all = err_all[sort_index]
+
+    pos_tmp = pos_all[:1]
+    val_tmp = val_all[:1]
+    err_tmp = err_all[:1]
+    num_tmp = np.array([1])
+    for pos, val, err in zip(pos_all[1:], val_all[1:], err_all[1:]):
+        if pos - pos_tmp[-1] < MOTOR_POS_PRECISION:
+            # the repeated motor position
+            val_tmp[-1] += val
+            err_tmp[-1] += err
+            num_tmp[-1] += 1
+        else:
+            # a new motor position
+            pos_tmp = np.append(pos_tmp, pos)
+            val_tmp = np.concatenate((val_tmp, val[None, :]))
+            err_tmp = np.concatenate((err_tmp, err[None, :]))
+            num_tmp = np.append(num_tmp, 1)
+
+    scan_into[scan_motor] = pos_tmp
+    scan_into["counts"] = val_tmp / num_tmp[:, None, None]
+    scan_into["counts_err"] = np.sqrt(err_tmp) / num_tmp[:, None, None]
+
+    scan_from["export"] = False
+
+    fname1 = os.path.basename(scan_into["original_filename"])
+    fname2 = os.path.basename(scan_from["original_filename"])
+    print(f'Merging scans: {scan_into["idx"]} ({fname1}) <-- {scan_from["idx"]} ({fname2})')
+
+
 def restore_scan(scan):
     if "merged_scans" in scan:
         for merged_scan in scan["merged_scans"]: