Piergiorgio Sartor <
piergiorgio.sartor.this.should.not.be.used@nexgo.REMOVETHIS.de> wrote:
On 01/08/2026 01.13, Maria Sophia wrote:
[...]
I'm under the impression there is some
confusion here.
To be expected considering who the OP is...
On the other hand, PRNU will have some
spatial statistical properties, even if
it is fixed for a given sensor.
Now, assuming we have some PRNU from some
unrelated sensor (meaning we can generate
a spatial noise with same statistical
properties), it would be possible to
consider to apply this noise ("apply", not
"add") to a given image.
This means the effective PRNU will be the
combination ("combination", not "sum") of
two PRNUs, resulting in a new fingerprint,
different from the original one.
So, de-noising is not really needed, but it
might be helpful to reduce / remove / modify
the original PRNU, so that the applied one
will be more evident.
The two main issues regarding PRNU that the OP has missed when jumping to conclusions are: 1) it is probabilitic, 2) it is comparative.
That means for 1) there's no guarantee that the noise in your camera
sensor is unique to you. It might be common, or very similar, to all
cameras of that model and batch. The statistical model is based on small samples of camera sensors so it isn't a globally accurate model.
For 2) that means it cannot state which device was used to take a photo
without having the device in question in your possession.
Just like ballistics. Once you have a suspect gun in your possession you
can make some assessment of the probability of whether that gun fired a particular round.
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