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
452dd755fc
First PRNU distance test
2024-03-22 11:58:34 +01:00
92ede944c7
Not satisfying due to zero offset
2024-03-22 11:42:47 +01:00
c287d5f0ef
Add an use toPilImage
2024-03-22 11:39:51 +01:00
674025fa62
First iteration of fake dataset generation
2024-03-22 11:20:07 +01:00
876ce96a58
Add datasets/fake/generate_dataset.py
2024-03-22 10:31:47 +01:00
408b7a2ba9
Add flat vision dataset size computation
...
It is about 8.7 GB.
2024-03-21 17:15:56 +01:00
