From the Sensor to Color Images

Losson, Olivier; Dinet, Éric

doi:10.1002/9781118562680.ch6

Cited by 5 publications

(2 citation statements)

References 29 publications

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“…Colour Correction In order to obtain a faithful representation of the colours as perceived by the observer, white balance adjusts colour intensities in such a way that achromatic objects from the real scene are rendered as such [32]. This is done by scaling each channel separately, thus also scaling differently the noise level of each channel.…”

Section: Raw Image Acquisitionmentioning

confidence: 99%

Non-Semantic Evaluation of Image Forensics Tools: Methodology and Database

Bammey¹,

Nikoukhah²,

Gardella³

et al. 2022

2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

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We propose a new method to evaluate image forensics tools, that characterizes what image cues are being used by each detector. Our method enables effortless creation of an arbitrarily large dataset of carefully tampered images in which controlled detection cues are present. Starting with raw images, we alter aspects of the image formation pipeline inside a mask, while leaving the rest of the image intact. This does not change the image's interpretation; we thus call such alterations "non-semantic", as they yield no semantic inconsistencies. This method avoids the painful and often biased creation of convincing semantics. All aspects of image formation (noise, CFA, compression pattern and quality, etc.) can vary independently in both the authentic and tampered parts of the image. Alteration of a specific cue enables precise evaluation of the many forgery detectors that rely on this cue, and of the sensitivity of more generic forensic tools to each specific trace of forgery, and can be used to guide the combination of different methods. Based on this methodology, we create a database and conduct an evaluation of the main state-of-the-art image forensics tools, where we characterize the performance of each method with respect to each detection cue. Check qbammey.github.io/trace for the database and code.GALILEO: How would it be if your Highness were now to observe these impossible as well as unnecessary stars through this telescope? THE MATHEMATICIAN: One might be tempted to reply that your telescope, showing something which cannot exist, may not be a very reliable telescope, eh?

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Section: Raw Image Acquisitionmentioning

confidence: 99%

Non-Semantic Evaluation of Image Forensics Tools: Methodology and Database

Bammey¹,

Nikoukhah²,

Gardella³

et al. 2022

2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

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show abstract

“…In order to obtain a faithful representation of the colours as perceived by the observer, colour intensities are adjusted in such a way that achromatic objects from the real scene are rendered as so [33]. This process is known as white balance and consists in scaling each channel's value by multiplying it by a constant.…”

Section: White Balancementioning

confidence: 99%

Non-Semantic Evaluation of Image Forensics Tools: Methodology and Database

Bammey,

Nikoukhah,

Gardella

et al. 2021

Preprint

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With the aim of evaluating image forensics tools, we propose a methodology to create forgeries traces, leaving intact the semantics of the image. Thus, the only forgery cues left are the specific alterations of one or several aspects of the image formation pipeline. This methodology creates automatically forged images that are challenging to detect for forensic tools and overcomes the problem of creating convincing semantic forgeries. Based on this methodology, we create the Trace database and conduct an evaluation of the main state-of-the-art image forensics tools.

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