一种基于特征空间分解的非对称鲁棒水印方法

针对数字图像的版权保护,提出一种基于特征空间分解的非对称数字水印方法,即对数字图像的特征空间分解,将水印嵌入到最少受图像改变影响的子空间,使嵌入的水印具有鲁棒性.同时,因水印嵌入矩阵(密钥)与提取矩阵(公钥)不同,可公开除密钥外所有其它信息.通过对特征子空间选取限制,算法具有高的检测概率和安全性,低的虚警概率.仿真得到的结果,表明了算法具有好的鲁棒性.

An Asymmetric Robust Watermarking Method Based on Feature Space Decomposing

To the problem of digital picture's copyright protection,we propose an asymmetric watermarking method based on feature space decomposing.Passing feature space decomposing of digital image,we obtain that the robustness of the approach lies in hiding a watermark in the subspace that is least susceptible to potential modification.In the same time,because we use different matrix operation to embed(secret key)and extract(public key)a watermark,we are able to release all information for the public,except the secret key.Through analysis and constraint the conditions of feature space,the algorithm we proposed can obtain a high detection probability and security,a low false alarm probability.The robustness of the asymmetric watermarking method is demonstrated by a kind of attacks through computer simulation.