论文标题

基于四元基因奇异值分解和系数对选择有效的稳健水印

Efficient Robust Watermarking Based on Quaternion Singular Value Decomposition and Coefficient Pair Selection

论文作者

Chen, Yong, Jia, Zhi-Gang, Peng, Ya-Xin, Peng, Yan

论文摘要

Quaternion单数值分解(QSVD)是一种可靠的数字水印技术,可以从低畸变的水印图像中提取高质量的水印。在本文中,进一步研究了QSVD技术,并提出了有效的强大水印方案。提出了改进的代数结构方法,以解决常规QSVD设计中发生“复杂性爆炸”的问题。通过将两种新策略纳入QSVD,即系数对选择和自适应嵌入,从而盲目传播秘密信息。与将水印嵌入单个假想单元中的常规QSVD不同,我们建议使用归一化互相关(NC)方法将水印自适应地嵌入最佳隐藏位置。这避免了与相关性较小的系数配对的选择,因此,它通过减少系数值的最大修饰来降低嵌入影响。通过这种方式,与常规QSVD相比,提出的水印策略避免了对单个彩色图像层的更多修改,并且可以观察到更好的水印图像的视觉质量。同时,自适应QSVD抵抗了一些常见的几何攻击,并提高了常规QSVD的鲁棒性。通过这些改进,我们的方法优于常规QSVD。还通过实验证明了它比其他最先进方法的优势。

Quaternion singular value decomposition (QSVD) is a robust technique of digital watermarking which can extract high quality watermarks from watermarked images with low distortion. In this paper, QSVD technique is further investigated and an efficient robust watermarking scheme is proposed. The improved algebraic structure-preserving method is proposed to handle the problem of "explosion of complexity" occurred in the conventional QSVD design. Secret information is transmitted blindly by incorporating in QSVD two new strategies, namely, coefficient pair selection and adaptive embedding. Unlike conventional QSVD which embeds watermarks in a single imaginary unit, we propose to adaptively embed the watermark into the optimal hiding position using the Normalized Cross-Correlation (NC) method. This avoids the selection of coefficient pair with less correlation, and thus, it reduces embedding impact by decreasing the maximum modification of coefficient values. In this way, compared with conventional QSVD, the proposed watermarking strategy avoids more modifications to a single color image layer and a better visual quality of the watermarked image is observed. Meanwhile, adaptive QSVD resists some common geometric attacks, and it improves the robustness of conventional QSVD. With these improvements, our method outperforms conventional QSVD. Its superiority over other state-of-the-art methods is also demonstrated experimentally.

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