Path: csiph.com!eternal-september.org!feeder.eternal-september.org!nntp.eternal-september.org!.POSTED!not-for-mail From: Piergiorgio Sartor Newsgroups: rec.photo.digital,alt.comp.os.windows-10,comp.lang.python Subject: Re: PSA Using Python Pillow to foil camera image PRNU fingerprinting Date: Sat, 1 Aug 2026 11:48:05 +0200 Organization: A noiseless patient Spider Lines: 65 Message-ID: References: <114en2t$7bu$1@nnrp.usenet.blueworldhosting.com> <114f0l7$1is0l$1@dont-email.me> <114frd8$2okp$1@nnrp.usenet.blueworldhosting.com> <114j5su$4kq$1@nnrp.usenet.blueworldhosting.com> <114j8pa$34k3s$2@dont-email.me> <114ja7g$2elo$1@nnrp.usenet.blueworldhosting.com> MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8; format=flowed Content-Transfer-Encoding: 7bit Injection-Date: Sat, 01 Aug 2026 09:51:45 +0000 (UTC) Injection-Info: dont-email.me; logging-data="3686669"; mail-complaints-to="abuse@eternal-september.org"; posting-account="U2FsdGVkX1812Xt2+hiPtTpsCSSQ8ZQz"; posting-host="d85e911b316adfc0232aa381e583327e" User-Agent: Mozilla Thunderbird Cancel-Lock: sha1:dKqOISWVZOAo2HwNgjDyEDbGmdA= sha256:gH+YBfqYZwuZjLdJ598ZO4saCaQYEbu0bNNDmdfM9NA= sha1:6dtYgcDBIbF5hUvORW3wlVO65Zo= sha256:Dw2MBqDjUhSQUy5sodEpembVOj+PQ/uUJK+HIGfzQ10= Content-Language: it, en-US In-Reply-To: <114ja7g$2elo$1@nnrp.usenet.blueworldhosting.com> Xref: csiph.com rec.photo.digital:244697 alt.comp.os.windows-10:194870 comp.lang.python:197850 On 01/08/2026 01.13, Maria Sophia wrote: [...] I'm under the impression there is some confusion here. De-noising algorithms, like BM3D or any de-noising auto-encoder, de-noise just one image. There is no temporal noise involved, it is only spatial, since the algorithms see only one, single, image. There are temporal de-noising algorithm which could be applied to video sequences, but this does not seem to be the case here. 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 point here is that the image content will not be altered too much, so quality will be somehow preserved. Different than blurring or resizing. If you do not like BM3D, you can look, as mentioned above, into de-noising auto-encoders. These will be even more aggressive in removing the PRNU content (maybe with more damage to the overall image). Finally, consider the "simple" case of generative algorithm (AI stuff, so to speak). These could (YMMV) generate image *without* any PRNU, similar or identical to the one taken with the camera. So, the fingerprint will be gone (maybe there will be another one from the AI). It seems to me there is a lot to explore way beyond the simple image modification algorithms. bye, -- piergiorgio