diff --git a/setup.py b/setup.py
index 8f998a5..10e365f 100644
--- a/setup.py
+++ b/setup.py
@@ -76,7 +76,7 @@
 packages = result
 
 setup (name = 'vstarstack',
-       version = '0.3.4',
+       version = '0.3.6',
        author='Vladislav Tsendrovskii',
        description = 'Stacking astrophotos',
        package_dir = {'vstarstack': 'src/vstarstack'},
diff --git a/src/vstarstack/library/movement/move_image.py b/src/vstarstack/library/movement/move_image.py
index 6c01b9d..468bcda 100644
--- a/src/vstarstack/library/movement/move_image.py
+++ b/src/vstarstack/library/movement/move_image.py
@@ -128,7 +128,7 @@ def move_dataframe(dataframe: DataFrame,
             else:
                 weight = np.ones(image.shape)
 
-        if channel in dataframe.links["saturation"]:
+        if "saturation" in dataframe.links and channel in dataframe.links["saturation"]:
             saturation_channel = dataframe.links["saturation"][channel]
             saturation, _ = dataframe.get_channel(saturation_channel)
         else:
diff --git a/src/vstarstack/library/stars/detect.py b/src/vstarstack/library/stars/detect.py
index 353ad76..651b8ee 100644
--- a/src/vstarstack/library/stars/detect.py
+++ b/src/vstarstack/library/stars/detect.py
@@ -15,8 +15,10 @@
 import math
 import numpy as np
 import cv2
+from scipy.ndimage import gaussian_filter
 import imutils
 import imutils.contours
+import matplotlib.pyplot as plt
 
 from skimage import measure
 
@@ -42,17 +44,17 @@ def calculate_brightness(image : np.ndarray, x : int, y : int, r : int):
     return brightness
 
 def _threshold(image, radius, ratio, safety_threshold):
-    filtered = cv2.GaussianBlur(image, (2*radius+1, 2*radius+1), 0)
-    mask = (image > filtered*ratio + safety_threshold).astype('uint8')
+    filtered = gaussian_filter(image, sigma=radius)
+    threshold = filtered*ratio + safety_threshold*np.amax(filtered)
+    mask = (image > threshold).astype('uint8')
     return mask
 
 def _find_stars(gray_image : np.ndarray):
     """Find stars on image"""
     shape = gray_image.shape
 
-    gray_image = (gray_image.astype(np.float32) / np.amax(gray_image) * 255).astype(np.uint8)
     gray_image = np.clip(gray_image, 0, None)
-    gray_image = cv2.GaussianBlur(gray_image, (3, 3), 0)
+    gray_image = gaussian_filter(gray_image, sigma=2)
 
     thresh = _threshold(gray_image, _detector_cfg["THRESHOLD_BLOCK_SIZE"],
                                     _detector_cfg["THRESHOLD_COEFF"],
diff --git a/src/vstarstack/tool/stars/config.py b/src/vstarstack/tool/stars/config.py
index f09c148..8a4d234 100644
--- a/src/vstarstack/tool/stars/config.py
+++ b/src/vstarstack/tool/stars/config.py
@@ -27,6 +27,7 @@
     },
     "use_angles": (bool, True),
     "brightness_over_neighbours": (float, 2.0),
+    "min_brightness" : (float, 0.01),
     "max_compares": (int, 0),
 }
 
diff --git a/src/vstarstack/tool/stars/detect.py b/src/vstarstack/tool/stars/detect.py
index 57fcb97..38553b9 100644
--- a/src/vstarstack/tool/stars/detect.py
+++ b/src/vstarstack/tool/stars/detect.py
@@ -97,7 +97,9 @@ def run(project: vstarstack.tool.cfg.Project, argv: list):
         mindist = project.config.stars.describe.mindist
 
     thr_coeff = project.config.stars.brightness_over_neighbours
-    detect.configure_detector(thresh_coeff=thr_coeff)
+    thr_safety = project.config.stars.min_brightness
+    logger.info(f"Threshold coefficient {thr_coeff}")
+    detect.configure_detector(thresh_coeff=thr_coeff, safety_threshold=thr_safety)
     if os.path.isdir(path):
         _process_dir(path, jsonpath, num_stars, mindist)
     else: