摘要
数字水印是数字作品版权保护的重要技术手段 ,DCT变换域盲图像水印算法是数字水印研究的主流之一 .该文通过分析盲水印检测与私有水印检测在理论模型上的本质区别 ,认为在水印研究中已被广泛使用的线性相关算法在盲水印检测中不再具有普遍适用的理论依据 .进而根据 DCT交流系数的拉普拉斯分布模型 ,提出了一种新的盲图像水印检测算法——符号相关算法 .通过计算渐进相对效率证明了该检测算法的高效性 ,针对典型攻击的实验结果表明该算法具有很好的鲁棒性 .
Digital watermarking is a key technique for protecting intellectual property of digital media. Due to the ability to detect watermark without the original image, blind watermarking is very useful if there are too many images to be authenticated. Since Cox et al. proposed a DCT-based spread spectrum approach to hide watermark, a lot of watermarking schemes in the DCT domain have been presented. Barni improved Cox's algorithm and made it a blind watermarking scheme by embedding the signature in the fixed position. But the watermark detection algorithm in is based on the calculation of the correlation coefficient between the image and the watermark in the DCT domain. In this paper, we began our analysis by posing the difference on mathematical models between private watermark detection and blind watermark detection. The watermark 'detection' in is not detecting weak signal in noise, but comparing watermark signal and its estimation. Based on this analysis, we point out that the linear correlation detector, which has been somewhat taken for granted in the previous literature in the private watermarking algorithms, would be optimal in blind watermark detection only if the host signal followed Gaussian distribution. After reviewing some statistical models which have been proposed to better characterize the DCT coefficients of images, we find that the popular Gaussian distribution is not accurate enough to model the peaky, heavy-tailed marginal distribution of DCT coefficients. So we devise and implement a new blind watermark detector--sign correlation detector based on the Laplacian distribution model of AC DCT coefficient. Computing result of asymptotic relative efficiency demonstrates that efficiency of sign correlation detector is much greater than that of linear correlation. A series of experiments also show that it is more robust than linear correlation detector. After compressing the watermarked image using JPEG standard with 75% quality, or filtering the watermarked image three times using median filter,
出处
《计算机学报》
EI
CSCD
北大核心
2001年第12期1279-1286,共8页
Chinese Journal of Computers
关键词
数字水印
盲图像水印检测算法
图像处理
符号相关算法
版权保护
digital watermark, Laplacian distribution, sign correlation detection, asymptotic relative efficiency
