From a8fa053687b09e0bf06aae0a331215711cb8c0b0 Mon Sep 17 00:00:00 2001
From: Benjamin Loison <12752145+Benjamin-Loison@users.noreply.github.com>
Date: Tue, 16 Apr 2024 03:02:58 +0200
Subject: [PATCH] #49: Get PRNU by using RAW images

---
 datasets/raise/extract_noise.py | 18 +++++++++++-------
 1 file changed, 11 insertions(+), 7 deletions(-)

diff --git a/datasets/raise/extract_noise.py b/datasets/raise/extract_noise.py
index 5e00882..72a80e0 100755
--- a/datasets/raise/extract_noise.py
+++ b/datasets/raise/extract_noise.py
@@ -33,10 +33,10 @@ if requiresRaiseFiltering:
 
     imagesFileNames = [imageFileName for imageFileName in tqdm(imagesFileNames, 'Filtering images') if files[imageFileName]['Device'] == 'Nikon D7000' and Image.open(f'{imagesFolderPath}/{imageFileName}').size == (4946, 3278)]
 
-maxGreen = None
+minGreen = 308#None
 
 def treatImage(imageFileName):
-    global mean, numberOfImagesInMean, maxGreen
+    global mean, numberOfImagesInMean, minGreen
     imageFilePath = f'{imagesFolderPath}/{imageFileName}'
     if imageFileName.endswith('.NEF'):
         with rawpy.imread(imageFilePath) as raw:
@@ -45,18 +45,22 @@ def treatImage(imageFileName):
             assert np.array_equal(raw.raw_pattern, np.array([[0, 1], [3, 2]], dtype = np.uint8))
             rawImageVisible = raw.raw_image_visible.copy()
             greenRawImageVisible = rawImageVisible[1::2, ::2]
-            greenRawImageVisibleMax = greenRawImageVisible.max()
-            if maxGreen is None or greenRawImageVisibleMax > maxGreen:
-                maxGreen = greenRawImageVisibleMax
-                print(f'{maxGreen=}')
-            imageNpArray = greenRawImageVisible
+            '''
+            greenRawImageVisibleMin = greenRawImageVisible.min()
+            if minGreen is None or greenRawImageVisibleMin < minGreen:
+                minGreen = greenRawImageVisibleMin
+                print(minGreen)
+            '''
+            imageNpArray = (greenRawImageVisible - minGreen) / (4908 - minGreen)
             # 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.
             #exit(1)
     else:
         imagePil = Image.open(imageFilePath)
         imageNpArray = img_as_float(np.array(imagePil))
     # As the arguments differ from a denoiser to the other should use a match instead.
     imageDenoisedNpArray = denoise(imageNpArray, rescale_sigma=True)
+    #print(imageNpArray, imageDenoisedNpArray)
     imageNoiseNpArray = imageNpArray - imageDenoisedNpArray
     if mean is None:
         mean = imageNoiseNpArray