Spatio-Temporal Just Noticeable Distortion Model Guided Video Watermarking
Spatio-Temporal Just Noticeable Distortion Model Guided Video Watermarking
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DOI：
10.4018/jdcf.2010100102
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发表时间：
2009-12
期刊：
影响因子：
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通讯作者：
Yaqing Niu;S. Krishnan;Qin Zhang
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文献类型：
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作者：
Yaqing Niu;S. Krishnan;Qin Zhang
感知视频水印需要充分利用人类视觉系统（HVS）研究的结果。由于运动是视频的一个特定特征，因此需要考虑时间 HVS 属性。在本文中，我们利用组合的时空可察觉失真（JND）模型，该模型结合了空间 CSF、时间调制因子、视网膜速度、亮度适应和对比度掩蔽来指导数字视频的水印。所提出的水印方案，其中表示附加准确感知可见性阈值的视觉模型被完全用于确定水印插入的场景驱动上限，使我们能够提供最大强度的透明水印。实验结果证实了我们组合的时空 JND 模型引导水印方案的性能得到了提高。我们的时空 JND 模型引导水印方案允许更高的注入水印能量而不损害图像质量，其鲁棒性比基于相关现有感知模型的其他算法要好得多。
Perceptual video watermarking needs to take full advantage of the results from human visual system (HVS) studies. Since motion is a specific feature of video, temporal HVS properties need to be taken into account. In this paper, we exploit a combined Spatio-Temporal Just Noticeable Distortion (JND) model which incorporates spatial CSF, temporal modulation factor, retinal velocity, luminance adaptation and contrast masking to guide watermarking for digital video. The proposed watermarking scheme, where visual models representing additional accurate perceptual visibility threshold are fully used to determine scene-driven upper bounds on watermark insertion, allows us to provide the maximum strength transparent watermark. Experimental results confirm the improved performance of our combined Spatio-Temporal JND model guided watermarking scheme. Our Spatio-Temporal JND model guided watermarking scheme which allows higher injected-watermark energy without jeopardizing picture quality performs much better on robustness than other algorithms based on the relevant existing perceptual models.