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摘要:
图像水印技术是一种在图像中嵌入被称为水印的版权标记,以证明图像版权归属的技术。利用图像纹理粗糙区域易于隐藏水印的优势,提出了一种基于图像纹理的自适应水印算法。首先,设计了一种能够真实反映图像纹理丰富程度的纹理度量方法,引入全局纹理值和局部纹理值的概念来综合分析图像纹理的分布情况;其次,利用滑动窗口和窗口内区域的局部纹理值,精确地获取图像的纹理粗糙区域,将水印嵌入在纹理粗糙区域中,保证嵌入水印图像的视觉质量;然后,通过多元回归分析,得到水印嵌入参数与纹理粗糙区域的全局纹理值和局部纹理值的函数关系,根据区域的纹理值自适应地调整水印的嵌入参数,最大限度地保证水印的不可见性,增强水印的鲁棒性;最后,通过在多个不重叠的纹理粗糙区域中嵌入相同的水印,进一步提高水印提取的准确率。在100幅自然场景图像上进行模拟实验,从不可见性、自适应性和鲁棒性三个方面证实了所提算法相比已有自适应水印算法的优越性。
Abstract:Watermarking is a technique of embedding a mark called a watermark in an image to prove the copyright of this image. This paper proposes an image texture based adaptive watermarking algorithm by taking advantage of the textured regions of an image being easy to hide the watermark. Firstly, a texture measurement method is proposed to reflect the richness of image's texture, and the concepts of global texture value and local texture value are introduced to comprehensively analyze the image texture distribution. The textured regions of an image are located by using the sliding window and judged by the local texture value of the inner window area, and then we only embed the watermark in the textured regions and ensure the visual quality of embedded watermark. The function relationship among the global texture value, the local texture value of the textured regions and the embedding parameter is obtained by multiple regression analysis. It can adaptively adjust the embedding parameters with the texture values of the regions to maximally enhance the imperceptibility and robustness of the watermark. Moreover, embedding the same watermark in multiple non-overlapping textured regions further improves the accuracy of the extracted watermark. The simulation experiments on 100 images show the superiority of the proposed method compared with the state-of-the-art methods in terms of imperceptibility, adaptivity and robustness.
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Key words:
- image watermarking /
- image texture /
- imperceptibility /
- robustness /
- adaptivity
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表 1 多元线性回归结果
Table 1. Multiple linear regression results
自变量 自变量系数 模型1 模型2 模型3 模型4 模型5 模型6 Tl 7.852*** 11.40*** 0 0 3.686*** 4.654*** Tl2 0 -0.204*** 0 0 0 -0.053 0 Tg 0 0 4.371*** 3.087*** 2.732*** 1.948*** Tg2 0 0 0 0.044 3* 0 0.025 1 常数 28.48*** 18.06*** 18.67*** 25.22*** 17.87*** 19.33*** R2/% 89 91 94.7 95.2 100 100 注:***表示p < 0.01, **表示p < 0.05, *表示p < 0.1,p值表示模型中自变量系数的标准差,反映该系数在模型中表现是否显著,***表示十分显著。 表 2 图像处理攻击后不同算法提取水印的BER值
Table 2. BERs of watermark extracted by different algorithms under image processing attacks
攻击类型 参数设置 BER/% TDSS DQAQT TBAQT JPEG压缩 30% 4.59 0.62 0.58 50% 2.89 0.08 0.08 70% 1.60 0 0 高斯噪声 0.04 7.45 3.58 0.06 0.03 5.88 2.22 0.02 0.02 4.28 0.68 0 椒盐噪声 0.048 3.24 0.27 0 0.04 2.91 0.15 0 0.035 2.83 0.08 0 均值滤波 3×3 2.56 0.01 5.75 中值滤波 3×3 3.37 0.03 3.18 直方图均衡 — 0.90 0.14 0 亮度改变 0.6 1.36 0 0 1.6 2.21 0.12 0 2 3.03 0.71 0.01 表 3 几何攻击后不同算法提取水印的BER值
Table 3. BERs of watermark extracted by different algorithms under geometric attacks
攻击类型 参数设置 BER/% TDSS DQAQT TBAQT 翻转 水平/垂直 1.56 0 0 旋转 90°整数倍 1.56 0 0 剪切 25% 2.12 0.04 0 32% 5.55 1.38 0 50% 9.63 4.84 0 遮挡 0.5 12.58 1.20 0 0.6 16.10 3.60 0 0.7 19.71 8.66 0.01 放缩 0.6 1.77 0 0 0.8 1.52 0 0 2.0 1.56 0 0 缩放 0.6 2.23 0 2.16 0.8 1.60 0 0 2.0 1.60 0 0 纵横比调整 0.8×1.4 1.62 0 0 1.8×0.7 1.63 0 0 -
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