Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Use mean as denoiser #57

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opened 2024-04-23 04:50:30 +02:00 by Benjamin_Loison · 2 comments
Benjamin_Loison commented 2024-04-23 04:50:30 +02:00
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RAISE flat field:

multiple_colors

Modified brightness and contrast:

image

Being able to explain why this method leads to an estimated PRNU with more color gradients as the original image.

RAISE flat field: ![multiple_colors](/attachments/f1f1fabb-971b-4e0d-afc8-af0bbebe1d01) Modified brightness and contrast: ![image](/attachments/25c31e4b-e3ae-4194-96db-7700bee58779) Being able to explain why this method leads to an estimated PRNU with more color gradients as the original image.
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Benjamin_Loison added the enhancementmedium prioritymedium labels 2024-04-23 04:50:30 +02:00
Benjamin_Loison pinned this 2024-04-23 04:50:49 +02:00
Benjamin_Loison commented 2024-04-24 14:20:08 +02:00
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Current issue is that in theory extracting noise by substracting the average image removes the PRNU, but as shown above we still observe patterns looking like unique artifacts. To avoid removing the PRNU as the image are quite smooth enough we will apply a Gaussian kernel to blur the image to remove the PRNU from the average image.

The good question is what sigma value is appropriate? Once will have mathematical metrics could benchmark.

Current issue is that in theory extracting noise by substracting the average image removes the PRNU, but as shown above we still observe patterns looking like unique artifacts. To avoid removing the PRNU as the image are quite smooth enough we will apply a Gaussian kernel to blur the image to remove the PRNU from the average image. The good question is what `sigma` value is appropriate? Once will have mathematical metrics could benchmark.
Benjamin_Loison commented 2024-04-27 14:57:43 +02:00
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Does not seem as precise as bilateral denoiser.

Mean denoiser:

image

Bilateral denoiser:

image

Source: issues/49#issuecomment-1693

Does not seem as precise as bilateral denoiser. Mean denoiser: ![image](/attachments/da53cc48-467e-4a33-bab7-803ad3e35ce9) Bilateral denoiser: ![image](/attachments/a9f58d89-613f-4f5e-9cab-cb5b6ee0ba7f) Source: [issues/49#issuecomment-1693](https://gitea.lemnoslife.com/Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones/issues/49#issuecomment-1693)
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Benjamin_Loison unpinned this 2024-04-27 14:58:02 +02:00
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Reference: Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones#57