diff --git a/datasets/raise/extract_noise.py b/datasets/raise/extract_noise.py
index 83c2f77..895488d 100755
--- a/datasets/raise/extract_noise.py
+++ b/datasets/raise/extract_noise.py
@@ -10,6 +10,7 @@ import csv
 import rawpy
 from utils import Color
 import matplotlib.pyplot as plt
+from scipy.ndimage import gaussian_filter
 
 imagesFolderPath = 'rafael/arw'
 imagesFolderPathFileName = imagesFolderPath.replace('/', '_')
@@ -100,7 +101,7 @@ def getImageNpArray(imageFileName, computeExtremes, color):
             maxColor = colorRawImageVisibleMax
         return
 
-    if imageFileName.endswith('.NEF') or imageFileName.endswith('.ARW'):
+    if (imageFileName.endswith('.NEF') or imageFileName.endswith('.ARW')) and denoiser != 'mean':
         imageNpArray = (imageNpArray - minColor) / (maxColor - minColor)
         # Pay attention to range of values expected by the denoiser.
         # Indeed if provide the thousands valued raw image, then the denoiser only returns values between 0 and 1 and making the difference between both look pointless.
@@ -128,7 +129,7 @@ def treatImage(imageFileName, computeExtremes = False, color = None):
         mean = ((mean * numberOfImagesInMean) + imageNoiseNpArray) / (numberOfImagesInMean + 1)
     numberOfImagesInMean += 1
 
-if minColor is None or maxColor is None:
+if (minColor is None or maxColor is None) and denoiser != 'mean':
     # Assuming same intensity scale across color channels.
     for imageFileName in tqdm(imagesFileNames, 'Computing extremes of images'):
         for color in colors:
@@ -148,8 +149,9 @@ if denoiser == 'mean':
     for color in colors:
         colorMean = None
         numberOfImagesInColorMean = 0
-        for imageFileName in tqdm(imagesFileNames, f'Computing mean of {color colored images'):
+        for imageFileName in tqdm(imagesFileNames, f'Computing mean of {color} colored images'):
             imageNpArray = getImageNpArray(imageFileName, False, color)
+            imageNpArray = gaussian_filter(imageNpArray, sigma = 5)
             if colorMean is None:
                 colorMean = imageNpArray
             else: