基于内容分类的乘性水印最优检测

Multiplicative Watermark Optimum Detection Based on Content Classification

提出了一种DCT域内基于内容分类的最优检测方法.该方法利用DCT变换中图像块低频能量的差异将DCT系数划分成平滑和纹理两类,并分别对这两类数据进行参数估计以实现基于最大似然比的最优检测.实验表明该方法较原有的整体参数估计和基于频段分类的参数估计在性能上有明显的提高.

A novel optimum detection method based on content classification is proposed, which uses the difference of energy sum of DCT coefficients in low and middle frequency to classify the image block into two classes. The optimum detection based on the maximum likelihood is realized through the parameter estimation of two kinds of image block DCT coefficients. The experiments show the performance of the new method is remarkably improved comparing with global and local parameter estimation based methods.