| 摘要: |
| 目前大多数水印算法采用线性相关的方法检测水印,但是,当原始媒体信号不服从高斯分布,或者水印不是以加嵌入方式嵌入到待保护的媒体对象中时,该方法存在一定的问题.数字水印的不可感知性约束决定了水印检测是一个弱信号检测问题,利用这一特性,首先从图像DCT(discrete cosine transform)交流变换系数的统计特性出发,应用广义高斯分布来建立其统计分布模型,然后将水印检测问题转化为二元假设检验问题,以非高斯噪声中弱信号检测的基本理论作为乘嵌入水印的理论检测模型,推导出优化的乘嵌入水印检测算法,并对检测算法进行了实验.结果表明,对于未知嵌入强度的乘水印的盲检测,提出的水印检测器具有良好的检测性能.因此,该检测器能在数字媒体数据的版权保护方面得到了实际的应用. |
| 关键词: 数字水印 离散余弦变换 广义高斯分布 乘嵌入 弱信号检测 |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.60273027(国家自然科学基金);the National Grand Fundamental Research 973 Program ofChina under Grant No.G1999035802(国家重点基础研究发展规划(973)) |
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| A Multiplicative Watermark Detection Algorithm for Digital Images in the DCT Domains |
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SUN Zhong-Wei,FENG Deng-Guo
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| Abstract: |
| Watermark detection plays a crucial role in digital watermarking. It has traditionally been tackled using correlation-based techniques. However, correlation-based detection is not the optimum choice either when the host media doesn't follow a Gaussian distribution or when the watermark is not embedded in the host media in an additive way. This paper addresses the problem of DCT (discrete cosine transform) domain multiplicative watermark detection for digital images. First, generalized Gaussian distributions are applied to statistically model the AC (alternative current) DCT coefficients of the original image. Then, the imperceptibility constraint of watermarking is exploited, and watermark detection is formulated as the problem of weak signal detection in non-Gaussian noise. A binary hypothesis test concerning whether or not an image is watermarked is established, and an optimum detection structure for blind watermark detection is derived. Experimental results indicate the superiority of the new detector in the case that the embedding strengths are unknown to the detector. Therefore, the proposed detector can be used for the copyright protection of the digital multimedia data. |
| Key words: digital watermarking discrete cosine transform generalized Gaussian distribution multiplicative embedding weak signal detection |
