Toward perceptual metrics for video watermark evaluation

Gelasca, E.D.; Ebrahimi, Touradj

doi:10.1117/12.512550

Cited by 21 publications

(14 citation statements)

References 15 publications

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“…Performance of the hiding scheme using different number of channels and varying compression parameters: "Bits per frame" and "FER" denote the per-frame data embedding rate and "frame error rate", respectively. The perceptual measures "Noise" (spatial noise) and "Flicker" 9 and PSNR (in dB) are averaged over all the frames. As seen from Table 1, using a higher number of channels, we are able to embed about 20% more data while the frame error rate is also reduced.…”

Section: Experiments and Resultsmentioning

confidence: 99%

Adaptive MPEG-2 video data hiding scheme

et al. 2007

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We have investigated adaptive mechanisms for high-volume transform-domain data hiding in MPEG-2 video which can be tuned to sustain varying levels of compression attacks. The data is hidden in the uncompressed domain by scalar quantization index modulation (QIM) on a selected set of low-frequency discrete cosine transform (DCT) coefficients. We propose an adaptive hiding scheme where the embedding rate is varied according to the type of frame and the reference quantization parameter (decided according to MPEG-2 rate control scheme) for that frame. For a 1.5 Mbps video and a frame-rate of 25 frames/sec, we are able to embed almost 7500 bits/sec. Also, the adaptive scheme hides 20% more data and incurs significantly less frame errors (frames for which the embedded data is not fully recovered) than the non-adaptive scheme. Our embedding scheme incurs insertions and deletions at the decoder which may cause de-synchronization and decoding failure. This problem is solved by the use of powerful turbo-like codes and erasures at the encoder. The channel capacity estimate gives an idea of the minimum code redundancy factor required for reliable decoding of hidden data transmitted through the channel. To that end, we have modeled the MPEG-2 video channel using the transition probability matrices given by the data hiding procedure, using which we compute the (hiding scheme dependent) channel capacity.

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Section: Experiments and Resultsmentioning

confidence: 99%

Adaptive MPEG-2 video data hiding scheme

et al. 2007

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“…Since the gradient of the difference between the original and translated values is low, the distortion has a small upper bound. The second effect of a video watermark is "flickering" [27] caused by the insertion of different watermarking data in successive frames. If the watermark remains constant, it can be removed by averaging a sequence of frames with varied backgrounds [24].…”

Section: Visibilitymentioning

confidence: 99%

VEIL: A System for Certifying Video Provenance

Gehani

Lindqvist

2007

Ninth IEEE International Symposium on Multimedia (ISM 2007)

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“…[9] PSNR 1.0000 0.1421 0.1705 -0.0091 Fan et al [7] 1.0000 0.8696 0.2959 Drelie et al [8] 1.0000 0.2043 Winkler et al [9] 1.0000 Table 1. Cross-correlations of metric outputs for JPEG2000 EBCOT-coded sequence at 0.50bpp.…”

Section: Flickering: Metrics and Causesmentioning

confidence: 99%

“…The last metric we evaluated was proposed by Winkler et al in [9]. It uses the 2D Fourier Transform to perform frequency analysis of the signal and then calculates two sub-metrics for low and high frequencies.…”

Section: Flickering: Metrics and Causesmentioning

confidence: 99%

Flicker Suppression in JPEG2000 using Segmentation-Based Adjustment of Block Truncation Lengths

Leontaris

Tonomura

Nakachi

et al. 2007

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07

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Flickering is a temporal visual artifact that affects compressed video. It is prominent in intra-frame video coders and is largely the result of content variations and quantization. We concentrate on flickering due to quantization. JPEG2000 uses Post-Compression Quantization which is applied through the EBCOT algorithm. EBCOT has been found, however, to cause significant flickering in the reconstructed video. In this work, we evaluate existing flicker metrics, investigate the causes of flicker, and propose a new rate-distortion optimal algorithm that suppresses flicker. The proposed algorithm suppresses temporal flicker at a negligible cost in spatial image quality.

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Toward perceptual metrics for video watermark evaluation

Cited by 21 publications

References 15 publications

Adaptive MPEG-2 video data hiding scheme

Adaptive MPEG-2 video data hiding scheme

VEIL: A System for Certifying Video Provenance

Flicker Suppression in JPEG2000 using Segmentation-Based Adjustment of Block Truncation Lengths

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