自嵌入全盲鲁棒水印量化算法

Self-embedding robust quantization-based watermarking algorithm with perfectly blind detection

为了提高图像水印的实用性,提出了一种自嵌入全盲鲁棒水印算法。首先,对原始图像进行DWT,将小波低频子带分成互不重叠的子块,对每个子块进行DCT,通过比较各个子块的直流系数与所有子块直流系数的均值之间的大小关系来产生特征水印序列,利用分段Logistic混沌序列对特征水印进行加密;然后,将加密后的特征水印序列通过奇偶量化规则自嵌入到原始图像小波低频子带每个子块的DCT低频系数中;最后,进行IDCT合成和IDWT产生含水印图像。该算法通过结合自嵌入加密的特征水印序列和盲提取认证水印序列达到全盲检测。实验结果表明,该算法对抵抗添加噪声、JPEG压缩及高斯低通滤波等常见的图像处理攻击均具有很强的鲁棒性。

In order to improve the practicality of the image watermarking , a self-embedding robust watermarking algorithm with perfectly blind detection is proposed . At first , the original image is conducted with DWT , and its low frequency wavelet band is split into non-overlapping blocks . Afterwards , each block is conducted with DCT , the feature watermark is derived from comparing the numerical relationship between DC coefficient of each block and average DC coefficient of all blocks . After encrypted by piece-wise Logistic chaos sequence , the feature watermark is self-embedded into each block′s low frequency DCT coefficients form the o-riginal image ’ s low frequency wavelet band based on the principle of odd-even quantization . Finally , the watermarked image is ob-tained after IDCT synthesis and IDWT . The algorithm achievs perfectly blind detection by combining self-embedding the encrypted feature watermark and blindly extracting authentication watermark . Experimental results show that the proposed algorithm has strong robustness to resist various general image processing attacks such as adding noise , JPEG compression , Gaussian low-pass filtering .