Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Make first rendering with both subgroups

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Benjamin Loison 2024-04-02 19:58:59 +02:00
parent ea00f42c58
commit f09665f856
Signed by: Benjamin_Loison
SSH Key Fingerprint: SHA256:BtnEgYTlHdOg1u+RmYcDE0mnfz1rhv5dSbQ2gyxW8B8
1 changed files with 26 additions and 4 deletions
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30
datasets/raise/split_and_compare_prnus_of_subgroups.py
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from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm
from skimage.restoration import denoise_tv_chambolle
import sys
sys.path.insert(0, '../../algorithms/image_utils/')
from image_utils import showImageWithMatplotlib
imagePath = 'flat-field/TIF/flat_001.tif'
imagePil = Image.open(imagePath).convert('F')
imageNpArray = np.array(imagePil)
showImageWithMatplotlib(imageNpArray)
NUMBER_OF_SUBGROUPS = 2
fig, axes = plt.subplots(NUMBER_OF_SUBGROUPS, 1)
fig.suptitle(f'PRNU estimation and comparison for {NUMBER_OF_SUBGROUPS} subgroups with different number of flat-images')
IMAGES_FOLDER = 'flat-field/TIF'
imagesFileNames = os.listdir(IMAGES_FOLDER)
numberOfImagesPerSubgroup = len(imagesFileNames) // NUMBER_OF_SUBGROUPS
# Assume random image order to not introduce a bias.
for subgroupIndex in range(NUMBER_OF_SUBGROUPS):
axis = axes[subgroupIndex]
imagesPrnuEstimateNpArray = []
for imageFileName in tqdm(imagesFileNames[numberOfImagesPerSubgroup * subgroupIndex : numberOfImagesPerSubgroup * (subgroupIndex + 1)]):
imagePath = f'{IMAGES_FOLDER}/{imageFileName}'
imagePil = Image.open(imagePath).convert('F')
imageNpArray = np.array(imagePil)
imagePrnuEstimateNpArray = imageNpArray - denoise_tv_chambolle(imageNpArray, weight=0.2, channel_axis=-1)
imagesPrnuEstimateNpArray += [imagePrnuEstimateNpArray]
cameraPrnuEstimateNpArray = np.array(imagesPrnuEstimateNpArray).mean(axis = 0)
axis.set_title(f'PRNU estimate for subgroup {subgroupIndex} with ')
axis.imshow(cameraPrnuEstimateNpArray)
plt.show()