Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Add color scales

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Benjamin Loison 2024-07-04 03:36:36 +02:00
parent dd7a6892e5
commit a17ec28cc3
Signed by: Benjamin_Loison
SSH Key Fingerprint: SHA256:BtnEgYTlHdOg1u+RmYcDE0mnfz1rhv5dSbQ2gyxW8B8
1 changed files with 9 additions and 4 deletions
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13
datasets/noise_free_test_images/estimate_prnu.py
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@ -34,7 +34,12 @@ SPLIT_N_X_N_S = [1, 2, 4]
fig, axes = plt.subplots(2, 4)
fig.suptitle('PRNU estimation with different number of images having Gaussian noise and Gaussian noised PRNU')
def axisImShow(axis, im):
imShow = axis.imshow(im)
plt.colorbar(imShow, label = 'Intensity', ax = axis, orientation = 'horizontal')
for splitNXNIndex, splitNXN in enumerate(SPLIT_N_X_N_S):
print(f'{splitNXN=}')
IMAGE_SIZE_SHAPE = [dimension // splitNXN for dimension in (704, 469)]
#prnuNpArray = 255 * randomGaussianImage(scale = PRNU_FACTOR, size = IMAGE_SIZE_SHAPE)
@ -67,16 +72,16 @@ for splitNXNIndex, splitNXN in enumerate(SPLIT_N_X_N_S):
axis = axes[0]
axis[0].set_title('First image without noise')
axis[0].imshow(imageWithoutPrnuNpArrayTile)
axisImShow(axis[0], imageWithoutPrnuNpArrayTile)
axis[1].set_title('Actual Gaussian noised PRNU')
axis[1].imshow(prnuNpArray)
axisImShow(axis[1], prnuNpArray)
axis[2].set_title('F. i. with G. n.')
axis[2].imshow(imageWithoutPrnuNpArray + imageNoise)
axisImShow(axis[2], imageWithoutPrnuNpArray + imageNoise)
axis[3].set_title('F. i. with G. n. and PRNU')
axis[3].imshow(imageWithoutPrnuNpArray + prnuNpArray + imageNoise)
axisImShow(axis[3], imageWithoutPrnuNpArray + prnuNpArray + imageNoise)
isFirstImage = False
#assert all([isIn256Range(extreme) for extreme in [imageWithPrnuNpArray.max(), imageWithPrnuNpArray.min()]]), 'Adding the PRNU resulted in out of 256 bounds image'