diff --git a/datasets/raise/attribute_source_camera.py b/datasets/raise/attribute_source_camera.py
index 254dd12..ae37b41 100755
--- a/datasets/raise/attribute_source_camera.py
+++ b/datasets/raise/attribute_source_camera.py
@@ -74,7 +74,7 @@ def getImagePrnuEstimateNpArray(singleColorChannelImages, multipleColorsImage, c
     return imagePrnuEstimateNpArray
 
 imagesCamerasFilePaths = {camera: [f'{IMAGES_CAMERAS_FOLDER[camera]}/{imagesCamerasFileName}' for imagesCamerasFileName in imagesCamerasFileNames[camera]] for camera in imagesCamerasFileNames}
-cameraColorMeans = {camera: getColorMeans(imagesCamerasFilePaths[camera], Color, DENOISER, minimalColorChannelCameraResolution) for camera in imagesCamerasFilePaths}
+cameraColorMeans = {camera: getColorMeans(imagesCamerasFilePaths[camera], Color, minimalColorChannelCameraResolution) for camera in imagesCamerasFilePaths}
 
 from utils import silentTqdm
 #tqdm = silentTqdm
diff --git a/datasets/raise/extract_noise.py b/datasets/raise/extract_noise.py
index 3ab80aa..be464bd 100755
--- a/datasets/raise/extract_noise.py
+++ b/datasets/raise/extract_noise.py
@@ -80,7 +80,7 @@ if (minColor is None or maxColor is None) and DENOISER != 'mean':
     print(f'{maxColor=}')
 
 if DENOISER == 'mean':
-    colorMeans = getColorMeans(imagesFileNames, COLORS, DENOISER)
+    colorMeans = getColorMeans(imagesFileNames, COLORS)
     for color in Color:
         colorMeans[color] = colorMeans[color]
         fileName = f'mean_{imagesFolderPathFileName}_{color}'
diff --git a/datasets/raise/utils.py b/datasets/raise/utils.py
index b7ed11f..d737f3c 100644
--- a/datasets/raise/utils.py
+++ b/datasets/raise/utils.py
@@ -132,12 +132,12 @@ def updateExtremes(imageNpArray, minColor, maxColor):
 def print(*toPrint):
     __builtin__.print(datetime.now(), *toPrint)
 
-def getColorMeans(imagesFileNames, colors, denoiser, singleColorChannelCropResolution = None):
+def getColorMeans(imagesFileNames, colors, singleColorChannelCropResolution = None):
     colorMeans = {}
     for color in colors:
         colorIterativeMean = iterativeMean()
         for imageFileName in tqdm(imagesFileNames, f'Computing mean of {color} colored images'):
-            imageNpArray = getImageNpArray(imageFileName, False, color, denoiser)
+            imageNpArray = getImageNpArray(imageFileName, False, color, 'mean')
             if singleColorChannelCropResolution is not None:
                 imageNpArray = getImageCrop(imageNpArray, singleColorChannelCropResolution)
             imageNpArray = gaussian_filter(imageNpArray, sigma = 5)