小波变换用于基于图像内容的自适应数字水印算法

为了提高在频率域嵌入水印抵抗攻击的能力,该文提出一种基于DWT的CBWM自适应数字水印嵌入算法,该算法依据离散小波变换域的水印嵌入策略:水印应当首先嵌入小波图像的低频系数中,若有剩余,再按小波图像频带重要性的排序,嵌入高频带中,并且水印嵌入到图像的低频系数和高频系数中时,需采用不同的嵌入强度;将水印嵌入到图像三级小波分解变换域的低频空间(LL3)的特征向量中,并且水印与特征向量两者正交。并且,其中水印的嵌入过程是自适应的,即先将小波系数组织成小波块,再依据纹理强弱对小波块分类,然后根据分类结果,将不同强度的水印分量嵌入到特征向量的不同分量中。此外,该算法对静止图像的水印检测是通过Neymann-Pearson决策准则来实现的。实验结果证明,该算法对滤波、噪声、几何变换、图像压缩、以及x-y方向修剪、StirMark攻击等都具有很好的抵抗能力;对裁剪和图像旋转也具有较好的鲁棒性。

Image Content-Based Adaptive Watermarking Arithmetic in DWT Domain

This paper proposes a new image content-based adaptive watermarking arithmetic(CBWM:Content-Based Watermarking Model)based on DWT (Discrete Wavelet Transform).The arithmetic takes the new watermarking-embedding strategy based on DWT domain that watermarks should be embedded in the low frequency space firstly,and the remains in the high frequency spaces according to their significance.And different embedding strength for watermarking should be applied to the low frequency space and the high ones respectively.In order to improve watermarking capability against attack in the frequency area,the embedded watermark is designed to be orthogonal to the feature vector of the low frequency space(LL3)in DWT area of the original image.Furthermore the process of watermarking embedding is quit adaptive,namely the algorithm organizes wavelet coefficients to form wavelet blocks and applies the texture characteristics to classify these wavelet blocks.And then watermark components with different strength are inserted into different weights of the feature vector.In addition,the arithmetic presents a statistical approach to watermark detection based on the Neymann-Pearson criterion and describes a method for computing the probability of false alarm and missing rejection during watermark detection.Experimental results show that the watermark arithmetic proposed in this paper is robust to filtering,noise adding,geometric transform,image compression and StirMark attack,and also has good robustness to cropping and image rotation.