Wan Wenbo, Li Wenqing, Liu Wenxiu, Diao Zihan, Zhan Yantong
School of Information Science and Engineering, Shandong Normal University, Jinan 250358, China.
Entropy (Basel). 2022 Jul 30;24(8):1051. doi: 10.3390/e24081051.
Robust quantization watermarking with perceptual JND model has made a great success for image copyright protection. Generally, either restores each color channel separately or processes the vector representation from three color channels with the traditional monochromatic model. And it cannot make full use of the high correlation among RGB channels. In this paper, we proposed a robust quaternion JND Model for color image watermarking (QuatJND). In contrast to the existing perceptual JND models, the advantage of QuatJND is that it can integrate quaternion representation domain and colorfulness simultaneously, and QuatJND incorporates the pattern guided contrast masking effect in quaternion domain. On the other hand, in order to efficiently utilize the color information, we further develop a robust quantization watermarking framework using the color properties of the quaternion DCT coefficients in QuatJND. And the quantization steps of each quaternion DCT block in the scheme are optimal. Experimental results show that our method has a good performance in term of robustness with better visual quality.
基于感知JND模型的鲁棒量化水印技术在图像版权保护方面取得了巨大成功。一般来说，要么分别恢复每个颜色通道，要么使用传统单色模型处理来自三个颜色通道的向量表示。并且它不能充分利用RGB通道之间的高度相关性。在本文中，我们提出了一种用于彩色图像水印的鲁棒四元数JND模型（QuatJND）。与现有的感知JND模型相比，QuatJND的优势在于它可以同时集成四元数表示域和色彩fulness，并且QuatJND在四元数域中纳入了模式引导的对比度掩蔽效应。另一方面，为了有效利用颜色信息，我们进一步开发了一种使用QuatJND中四元数DCT系数的颜色属性的鲁棒量化水印框架。并且该方案中每个四元数DCT块的量化步长是最优的。实验结果表明，我们的方法在鲁棒性方面具有良好的性能，同时具有更好的视觉质量。
