Commit Graph

56 Commits

Author SHA1 Message Date
d3af12ce3e
Try to have clear figure for thesis audition 2024-04-03 15:20:24 +02:00
aafb7ebc92
Plot an exhaustive curve to make sure that results are not just by chance 2024-04-02 23:58:41 +02:00
631ed6de34
#31: Establish expected wanted results about finding an identical PRNU for both subgroups 2024-04-02 21:05:15 +02:00
f09665f856
Make first rendering with both subgroups 2024-04-02 19:58:59 +02:00
ea00f42c58
Add datasets/raise/split_and_compare_prnus_of_subgroups.py 2024-04-02 18:45:40 +02:00
90a806a7e2
Move webpage articles to datasets/raise/website/ 2024-04-02 18:31:27 +02:00
0d6a956db8
Shorten figure titles 2024-04-02 11:03:47 +02:00
f0db61efe2
Make single figure to compare multiple splitNXN values 2024-03-29 13:47:27 +01:00
81852d5dc6
Make Gaussian noise in getPrnuShownAsSuch only on text 2024-03-29 13:22:36 +01:00
ec7c5c6688
Add gaussianNoise to getPrnuShownAsSuch but applies on the whole PRNU image 2024-03-29 13:16:50 +01:00
2d96bdc225
Not correct generalized SPLIT_N_X_N due to imageWithoutPrnuNpArrayTile 2024-03-29 13:11:24 +01:00
96bbd50a3b
Generalize with a partial image SPLIT_N_X_N 2024-03-29 12:57:56 +01:00
4bf9ef8206
Add splitNxN compatible with 1 and 4 2024-03-29 12:44:42 +01:00
60eceb575e
Simplify grayscale rendering 2024-03-29 12:16:13 +01:00
b375acbb3a
Use v{min,max} for enforcing matplotlib colormap
If it proceeds linearly to *covers the complete value range of the supplied data* then doing so is unnecessary and even if it is another not very different scale transformation then it is still fine for my goal.
2024-03-29 12:11:41 +01:00
5fa61f7ff8
Make PRNU compatible with 4x4 split 2024-03-29 11:23:48 +01:00
8351e46437
Comparison of an image without and with Gaussian noise and PRNU 2024-03-29 01:55:46 +01:00
2f66e82f22
Show both RMS and RMS normalized 2024-03-29 01:47:01 +01:00
3ccec5bbd0
Add RMS computation 2024-03-29 01:35:48 +01:00
f297060f42
Split images in 4x4 to increase PRNU estimation accuracy 2024-03-29 01:21:26 +01:00
9b57d3441c
Render PRNU estimate taking into account all images 2024-03-29 01:10:31 +01:00
d59a251b1f
Revert to some extent previous commit 2024-03-29 01:07:48 +01:00
4382b3d649
Add PRNU_FACTOR 0.1 and 0.01 view on a single figure 2024-03-29 01:05:28 +01:00
dfe2540c02
Apply Context-Adaptive Interpolator 2024-03-29 00:06:13 +01:00
9a3cfd7ba1
Add PRNU showing such 2024-03-28 22:24:16 +01:00
ba5a1b742b
#24: Make executions reproducible 2024-03-28 22:20:40 +01:00
a99e942d3a
Add datasets/noise_free_test_images/estimate_prnu.py 2024-03-28 17:06:58 +01:00
0953fb7475
Add issue reference to datasets/fake/generate_dataset.py 2024-03-28 17:06:36 +01:00
82e7026264
Add algorithms/image_utils/image_utils.py and move there randomGaussianImage and showImageWithMatplotlib 2024-03-28 16:32:38 +01:00
70ccb094d5
Rename randomImage to randomGaussianImage 2024-03-28 16:18:32 +01:00
64eaeddf98
Update annotations 2024-03-28 15:26:57 +01:00
18d34a3101
Add datasets/noise_free_test_images/no_noise_images.zip.txt 2024-03-28 15:25:21 +01:00
cbc778c4dc
Move datasets/noise_free_test_images/noise_free_test_images.{pdf.txt,xopp.xml} to datasets/noise_free_test_images/webpage/ 2024-03-28 15:22:28 +01:00
5af7afaf75
Add datasets/noise_free_test_images/ 2024-03-28 15:03:57 +01:00
cfe718da7d
Make x-axis logarithmic 2024-03-26 02:32:03 +01:00
2bc13c5949
#21: Make a RMS curve depending on the number of images considered for the mean 2024-03-26 01:59:22 +01:00
c2862eaf43
#21: Incorrect mean, as it is a RMS mean, not a mean of images 2024-03-26 01:55:08 +01:00
f181a3498c
Correct Image wuthout PRNU rendering and precise that it is the first image 2024-03-26 01:45:47 +01:00
03f52a5bd1
Finish Matplotlib figure showing PRNU estimation by averaging 2024-03-25 20:45:51 +01:00
2baf9c3000
Add and use rmsDiffNumpy 2024-03-25 20:14:33 +01:00
7c7cbad0ef
Rename rmsdiff to rmsDiffPil 2024-03-25 20:01:51 +01:00
8b0b58953d
WIP: Matplotlib figure showing PRNU estimation by averaging
Committed to showcase
Benjamin_Loison/Pillow#4.
2024-03-25 19:45:46 +01:00
044d25cbaa
Add and use showImageWithMatplotlib 2024-03-25 18:37:09 +01:00
8575da5b1d
WIP: Getting PRNU by averaging on fake dataset 2024-03-25 17:45:01 +01:00
cf22ff2694
Add comments 2024-03-22 12:59:52 +01:00
d818714344
CAI over images mean does not seem better 2024-03-22 12:57:24 +01:00
464e43861b
Prefer *mean* over *average* 2024-03-22 12:54:34 +01:00
41926663b7
Correct a typo but PRNU classifier still looking random 2024-03-22 12:51:34 +01:00
36f5b69f5e
First PRNU classifier acting randomly it seems 2024-03-22 12:46:13 +01:00
a9adf2d53d
Compare RMS difference between average images and the average CAI images
#9 (comment)
2024-03-22 12:11:26 +01:00