diff --git a/datasets/raise/attribute_source_camera.py b/datasets/raise/attribute_source_camera.py
index 05b583f..254dd12 100755
--- a/datasets/raise/attribute_source_camera.py
+++ b/datasets/raise/attribute_source_camera.py
@@ -3,7 +3,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
 from tqdm import tqdm
-from utils import denoise, iterativeMean, getColorChannel, escapeFilePath, Color, mergeSingleColorChannelImagesAccordingToBayerFilter, rescaleRawImageForDenoiser, updateExtremes, saveNpArray, getColorMeans
+from utils import denoise, iterativeMean, getColorChannel, escapeFilePath, Color, mergeSingleColorChannelImagesAccordingToBayerFilter, rescaleRawImageForDenoiser, updateExtremes, saveNpArray, getColorMeans, getImageCrop
 import sys
 import os
 import random
@@ -60,7 +60,7 @@ def getImageFilePath(camera, cameraImageIndex):
 
 def getSingleColorChannelImages(camera, cameraImageIndex):
     imageFilePath = getImageFilePath(camera, cameraImageIndex)
-    singleColorChannelImages = {color: rescaleIfNeeded(getColorChannel(imageFilePath, color)[:minimalColorChannelCameraResolution[0],:minimalColorChannelCameraResolution[1]], minColor, maxColor) for color in Color}
+    singleColorChannelImages = {color: rescaleIfNeeded(getImageCrop(getColorChannel(imageFilePath, color), minimalColorChannelCameraResolution), minColor, maxColor) for color in Color}
     return singleColorChannelImages
 
 def getMultipleColorsImage(singleColorChannelImages):
@@ -74,8 +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}
-#print(imagesCamerasFilePaths)
-cameraColorMeans = {camera: getColorMeans(imagesCamerasFilePaths[camera], Color, DENOISER) for camera in imagesCamerasFilePaths}
+cameraColorMeans = {camera: getColorMeans(imagesCamerasFilePaths[camera], Color, DENOISER, minimalColorChannelCameraResolution) for camera in imagesCamerasFilePaths}
 
 from utils import silentTqdm
 #tqdm = silentTqdm
diff --git a/datasets/raise/utils.py b/datasets/raise/utils.py
index 4121024..b7ed11f 100644
--- a/datasets/raise/utils.py
+++ b/datasets/raise/utils.py
@@ -132,12 +132,14 @@ def updateExtremes(imageNpArray, minColor, maxColor):
 def print(*toPrint):
     __builtin__.print(datetime.now(), *toPrint)
 
-def getColorMeans(imagesFileNames, colors, denoiser):
+def getColorMeans(imagesFileNames, colors, denoiser, 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)
+            if singleColorChannelCropResolution is not None:
+                imageNpArray = getImageCrop(imageNpArray, singleColorChannelCropResolution)
             imageNpArray = gaussian_filter(imageNpArray, sigma = 5)
             colorIterativeMean.add(imageNpArray)
         colorMeans[color] = colorIterativeMean.mean
@@ -156,3 +158,7 @@ def getImageNpArray(imageFilePath, computeExtremes, color, denoiser):
         # 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.
     return imageNpArray
+
+def getImageCrop(image, cropResolution):
+    imageCrop = image[:cropResolution[0], :cropResolution[1]]
+    return imageCrop