diff --git a/datasets/raise/attribute_source_camera.py b/datasets/raise/attribute_source_camera.py
index e7f5f7e..7643c04 100755
--- a/datasets/raise/attribute_source_camera.py
+++ b/datasets/raise/attribute_source_camera.py
@@ -67,6 +67,12 @@ def getMultipleColorsImage(singleColorChannelImages):
     multipleColorsImage = mergeSingleColorChannelImagesAccordingToBayerFilter(singleColorChannelImages)
     return multipleColorsImage
 
+def getImagePrnuEstimateNpArray(singleColorChannelImages, multipleColorsImage):
+    singleColorChannelDenoisedImages = {color: denoise(singleColorChannelImages[color], DENOISER) for color in Color}
+    multipleColorsDenoisedImage = mergeSingleColorChannelImagesAccordingToBayerFilter(singleColorChannelDenoisedImages)
+    imagePrnuEstimateNpArray = multipleColorsImage - multipleColorsDenoisedImage
+    return imagePrnuEstimateNpArray
+
 from utils import silentTqdm
 #tqdm = silentTqdm
 
@@ -84,10 +90,7 @@ for computeExtremes in tqdm(([True] if minColor is None or maxColor is None else
                 singleColorChannelImages = getSingleColorChannelImages(camera, numberOfTrainingImages + cameraTestingImageIndex)
                 multipleColorsImage = getMultipleColorsImage(singleColorChannelImages)
 
-                # Should make a function
-                singleColorChannelDenoisedImages = {color: denoise(singleColorChannelImages[color], DENOISER) for color in Color}
-                multipleColorsDenoisedImage = mergeSingleColorChannelImagesAccordingToBayerFilter(singleColorChannelDenoisedImages)
-                imagePrnuEstimateNpArray = multipleColorsImage - multipleColorsDenoisedImage
+                imagePrnuEstimateNpArray = getImagePrnuEstimatedNpArray(singleColorChannelImages, multipleColorsImage)
 
                 cameraTestingImagesNoise[camera] = cameraTestingImagesNoise.get(camera, []) + [imagePrnuEstimateNpArray]
     for cameraTrainingImageIndex in tqdm(range(minimumNumberOfImagesCameras if computeExtremes else numberOfTrainingImages), 'Camera training image index'):
@@ -99,10 +102,8 @@ for computeExtremes in tqdm(([True] if minColor is None or maxColor is None else
                 minColor, maxColor = updateExtremes(multipleColorsImage, minColor, maxColor)
                 continue
 
-            singleColorChannelDenoisedImages = {color: denoise(singleColorChannelImages[color], DENOISER) for color in Color}
-            multipleColorsDenoisedImage = mergeSingleColorChannelImagesAccordingToBayerFilter(singleColorChannelDenoisedImages)
+            imagePrnuEstimateNpArray = getImagePrnuEstimatedNpArray(singleColorChannelImages, multipleColorsImage)
 
-            imagePrnuEstimateNpArray = multipleColorsImage - multipleColorsDenoisedImage
             cameraIterativeMean = camerasIterativeMean[camera]
             cameraIterativeMean.add(imagePrnuEstimateNpArray)
             if cameraIndex == numberOfCameras - 1: