Adaptively Imperceptible Video Watermarking Algorithm Using Entropy Model
基于熵模型的高透明性自适应视频水印算法

An adaptively imperceptible video watermarking algorithm using entropy model is proposed. This algorithm works by first combining the Human Visual System (HVS) with block-matching techniques to obtain motion-related information. It then uses entropy model to statistically analyze the obtained information, and eventually establish a set of non-linear formulas based on HVS and motion information. Based on the contents of video frames, this set of non-linear formulas can adaptively calculate the maximum strength of every block. Experimental results show that using entropy model and non-linear formulas can significantly improve watermarking imperceptibility, effectively resist common attacks for video watermarking, and consequently achieve higher robustness.