Analysis of denoising filters for photo response non uniformity noise extraction in source camera identification

Identification of the source that has generated a digital content is considered one of the main open issues in multimedia forensics community. The extraction of photo-response non-uniformity (PRNU) noise has been so far indicated as a mean to identify sensor fingerprint. Such a fingerprint can be estimated from multiple images taken by the same camera by means of a denoising filtering operation. This paper presents an analysis of the performances of different denoising filters based on diverse noise models when applied for digital camera tracking. In particular, a digital filter, based on a signal-dependent noise model, is introduced and compared with others commonly adopted for this purpose. A theoretical framework and experimental results are provided and discussed.