摘要
为准确识别数字媒体的版权,更好地提高半脆弱水印的透明性和鲁棒性,提出离散小波变换域中基于人眼视觉特性模型的特征参数及其表示方法,给出适用于一般变换域参数调整的量化中心极限定理,使得在动态量化过程中嵌入的半脆弱水印能够达到最大的鲁棒性。实验表明,算法生成的载体图像透明性好,对常见的JPEG压缩、噪声迭加和平滑滤波等图像处理操作具有较好的鲁棒性,可嵌入的水印信息量大,并能准确确定恶意攻击的位置。
In order to improve the invisibility and the robustness of semi-fragile watermark, this paper brings up characteristic and representation in DWT transform domain based on visual features model, and puts forward the quantized central limit theorem which applies to adjust the coefficients in general transform domain. These all make semi-fragile watermark embedded through dynamic quantization achieve the greatest robustness. It leads up to the better invisibility of carrier image, the better robustness to the image processing, such as JPEG compression, noise adding, filtering, and the larger amount of embedded information. What's more, it can ascertain the position of vicious attack exactly. The speed of this algorithm is also high.
出处
《计算机工程》
CAS
CSCD
北大核心
2008年第11期146-148,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60373000)
中南林业科技大学青年科学基金资助项目(061018
06Y003)
关键词
半脆弱水印
视觉特性模型
量化中心极限定理
动态量化
semi-fragile watermark
visual features model
quantized central limit theorem
dynamic quantization