Multimedia source identification using an improved weight photo response non-uniformity noise extraction model in short compressed videos

Su, Kaiqing; Tian, Nili; Pan, Qing

doi:10.1016/j.fsidi.2022.301473

Cited by 4 publications

(6 citation statements)

References 29 publications

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“…The identification capabilities of the proposed PRNU extraction model are evaluated in this paper by juxtaposing it with the 11 cutting-edge PRNU extraction algorithms that are currently in operation. They are the Basic algorithm, 4 MLE algorithm, 5 BM3D algorithm, 6 PCAI8 algorithm, 40 CAGIF algorithm, 7 WeightPRNU algorithm, 22 SDA algorithm, 12 DTCWT algorithm, 11 MPR algorithm, 14 DHDN algorithm, 15 and VST algorithm 25 …”

Section: Experiments and Analysismentioning

confidence: 99%

“…The quality of the fingerprint estimated by P-frames is contingent on its position within the GOP. Su et al 25 suggested a multi-scale iterative least-squares filtering algorithm that is predicated on variance-stabilized transformation (VST) for the extraction of noise residuals from video frames. Then, they used a quantization parameter (QP) weighting method to estimate PRNU noise, thereby improving the source camera identification performance of short compressed videos.…”

Section: Related Workmentioning

confidence: 99%

“…The quality of the fingerprint estimated by P-frames is contingent on its position within the GOP. Su et al 25 . suggested a multi-scale iterative least-squares filtering algorithm that is predicated on variance-stabilized transformation (VST) for the extraction of noise residuals from video frames.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Double-weighted photo response non-uniformity extraction model based on multi-scale neighborhood shrinkage and structural filtering for YouTube compressed videos

Tian,

Luo,

Pan

2024

J. Electron. Imag.

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Photo response non-uniformity (PRNU), a unique trait of image sensors, can efficiently trace the camera source of a digital video. In response to the poor identification effect of network compression subsampling videos, a multi-scale neighborhood value shrinkage filtering algorithm based on Stein's unbiased risk estimation and an adaptive edge structure-preserving smoothing filtering algorithm are proposed, and a double-weighted PRNU extraction model is constructed. This model first performs a multi-scale transformation based on the dual-tree complex wavelet of the video frame that skips the loop filter, uses the multi-scale neighborhood value shrinkage filtering algorithm based on Stein's unbiased risk estimation to estimate all highfrequency sub-bands, obtains the noise residual, and uses the adaptive edge structure-preserving smoothing filter to smooth the complex noise residual. The maximum likelihood estimation method of the double-weight coefficient matrix based on the noise variance and quantization parameters is used to aggregate the noise residuals to obtain the PRNU. Verification is carried out on the public Vision database. The proposed model outperforms the current PRNU extraction model in source identification of compressed videos, as evidenced by the receiver operating characteristic curve, area under the curve, and Kappa coefficient values. It exhibits an accuracy rate that surpasses the best competing algorithm by 17.4%.

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Section: Experiments and Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Double-weighted photo response non-uniformity extraction model based on multi-scale neighborhood shrinkage and structural filtering for YouTube compressed videos

Tian,

Luo,

Pan

2024

J. Electron. Imag.

Self Cite

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show abstract

“…Strategies such as the removal of post-decoding artifacts or selective utilization of macroblocks were proposed in other studies 12,13 to enhance the accuracy of PRNU estimation by mitigating the detrimental effects of H.264 and H.265 video compression standards. A novel video forensics method, considering both camera roll and I-frames of videos to improve processing accuracy and time, was proposed by Yang et al 14 Su et al 15 solved the problem of further compression caused by videos uploaded to social networking sites by proposing a weighted PRNU extraction model based on variancestabilized transform multi-scale iterative least squares filtering and these techniques are beneficial for short video recognition.…”

Section: Introductionmentioning

confidence: 99%

“…A novel video forensics method, considering both camera roll and I-frames of videos to improve processing accuracy and time, was proposed by Yang et al 14 . Su et al 15 . solved the problem of further compression caused by videos uploaded to social networking sites by proposing a weighted PRNU extraction model based on variance-stabilized transform multi-scale iterative least squares filtering and these techniques are beneficial for short video recognition.…”

Section: Introductionmentioning

confidence: 99%

Stabilized videos source identification method based on undecimated dual-tree complex wavelet transform and Bayesian adaptive direct search algorithm

Tian,

Lin,

Pan

2023

J. Electron. Imag.

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The widely adopted video stabilization techniques in imaging devices have become a bottleneck that limits the performance of source camera identification (SCI) based on photo-response non-uniform (PRNU) noise. Affine transformations in the stabilized video, including scaling, translation, and rotation, introduce varying degrees of distortion to the PRNU pattern across frames, which lead to a degradation of accuracy and prolonged matching time in SCI methods. To address these issues, we propose a stabilized video source identification method that combines the undecimated dual-tree complex wavelet transform (UDTCWT) with the Bayesian adaptive direct search (BADS) algorithm. First, decoded frames are obtained by skipping the loop filter in the video codec to preserve more PRNU. Then, a PRNU extraction algorithm based on the UDTCWT is utilized to filter out more reliable PRNU from the decoded frames. Finally, the distorted PRNU is optimized and recovered by the affine transformation model with the BADS. Experiments on public datasets show that the proposed method outperforms state-of-the-art methods in terms of matching speed and accuracy.

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An improved PRNU noise extraction model for highly compressed image blocks with low resolutions

Tian,

Qiu,

Pan

2024

Multimed Tools Appl

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Multimedia source identification using an improved weight photo response non-uniformity noise extraction model in short compressed videos

Cited by 4 publications

References 29 publications

Double-weighted photo response non-uniformity extraction model based on multi-scale neighborhood shrinkage and structural filtering for YouTube compressed videos

Double-weighted photo response non-uniformity extraction model based on multi-scale neighborhood shrinkage and structural filtering for YouTube compressed videos

Stabilized videos source identification method based on undecimated dual-tree complex wavelet transform and Bayesian adaptive direct search algorithm

An improved PRNU noise extraction model for highly compressed image blocks with low resolutions

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