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.
Analysis of Denoising Filters for Photo Response Non Uniformity Noise Extraction in Source Camera Identification
CALDELLI R;
2009-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
