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计算机工程

• 安全技术 • 上一篇    下一篇

基于图像纹理复杂度的小波域数字水印算法

肖振久1,2，田淑娇1，陈 虹1   

  1. (1. 辽宁工程技术大学软件学院，辽宁 葫芦岛 125105；2. 中国传媒大学计算机学院，北京 100024)
  • 收稿日期:2013-04-17 出版日期:2014-06-15 发布日期:2014-06-13
  • 作者简介:肖振久(1968－)，男，副教授、博士，主研方向：网络与信息安全，数字版权管理；田淑娇，硕士研究生；陈 虹，副教授、硕士。
  • 基金项目:
    国家自然科学基金资助项目(61103199)；北京市自然科学基金资助项目(4112052)。

Wavelet Domain Digital Watermarking Algorithm Based on Image Texture Complexity

XIAO Zhen-jiu 1,2, TIAN Shu-jiao 1, CHEN Hong 1   

  1. (1. School of Software, Liaoning Technical University, Huludao 125105, China; 2. School of Computer, Communication University of China, Beijing 100024, China)
  • Received:2013-04-17 Online:2014-06-15 Published:2014-06-13

PDF

785

被引次数

13 | 2

摘要： 针对水印信息嵌入量小、鲁棒性弱、遮蔽性差的问题，提出一种基于图像纹理复杂度的小波域人类视觉系统的水印算法。该算法将载体图像进行分块，计算每块的图像熵，并根据图像熵对载体图像的纹理特征区域进行分类，不同纹理特征水印的嵌入量不同。利用Logistic映射对水印信号进行置乱变换，将水印信号嵌入到二层离散小波变换的低频系数中，并利用小波域人类视觉模型控制水印的嵌入强度。在提取水印时，通过水印误码率和峰值信噪比评价水印质量。实验结果表明，该算法能抵抗噪声干扰、裁剪和密钥攻击，水印图像具有较强的鲁棒性和良好的遮蔽性。

关键词: 纹理复杂度, Logistic映射, 离散小波变换, 人类视觉系统, 鲁棒性, 遮蔽性

Abstract: For a small amount of the watermark information embedding, the robustness of the watermark and the poorer shielding, this paper proposes a watermark algorithm based on image texture complexity in the wavelet domain, which is according to the characteristics of the Human Visual System(HVS). The algorithm separates the texture regions by using the image entropy, and different texture is embedded by different amount of watermark. In this algorithm, the watermark image being embedded is transformed with Logistic mapping, and the watermark signal is embedded into the low frequency coefficients of the Discrete Wavelet Transform(DWT) transform, and controls the watermark embedding strength by using the human visual system. The Bit Error Ratio(BER) and Peak Signal-to-noise Ratio(PSNR) are used to evaluate the algorithm. Experimental results show that this algorithm can resist noise, filtering, lossy compression, cutting, key attacks, and other common attacks. It has a better robustness, and performs excellent concealment properties.

Key words: texture complexity, Logistic mapping, Discrete Wavelet Transform(DWT), Human Visual System(HVS), robustness, concealment property

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