期刊
IEEE SIGNAL PROCESSING LETTERS
卷 23, 期 5, 页码 693-697出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2016.2549059
关键词
Digital forensics; maximum likelihood estimation (MLE); photo response nonuniformity (PRNU); Poisson process; raw data; source identification
资金
- Department of Electronics and Information Technology (DeitY), Government of India
Photo response nonuniformity (PRNU) is consider as reliable camera fingerprint for identifying source of a digital images. Digital cameras use various image processing operations to map linear color measurements (raw data) into nonlinear narrow gamut image. This nonlinear transformation affects estimation of PRNU. To undo the effect of nonlinear transformation, in this letter, we propose to estimate PRNU from probabilistically obtained raw values. Since not all cameras provide raw values as their output, we propose to compute estimate of raw values from the JPEG images using probabilistic color derendering procedure. The estimated raw values are modeled as a Poisson process and then maximum likelihood estimation (MLE) is used for PRNU estimation. The experimental results show that, the digital camera identification using our proposed PRNU estimate is better than using other popular PRNU estimate.
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