Robust Adaptive Video Watermarking Algorithm based on Dual Transform Domains

In this paper, we propose a robust video watermarking algorithm based on dual transform domain using the adaptive quantization method. In order to increase the robustness of watermark, Particle Swarm Optimization algorithm is used for embedding watermarks. Firstly, one-level wavelet decomposition is employed for the two-dimensional carrier signal by using the characteristics of the wavelet multi-resolution analysis, and then the lowfrequency and middle-frequency coefficients are extracted. After dividing the coefficients into small blocks, discrete cosine transform is applied to each block coefficient. Then, the adaptive quantization algorithm is designed. The optimal embedding positions in the two dimensional space of the carrier signal are determined dynamically by using Particle Swarm Optimization algorithm, and the coefficients in the optimal embedding positions are also extracted. According to the characteristics of these coefficients, the optimal quantization step sizes are determined dynamically in three dimensional space. Finally, the watermark is embedded into watermarking vector adaptively by using the optimal embedding positions and optimal quantization step sizes, then the watermarked vector will be received. The experimental results show that compared with traditional watermark algorithms, the presented robust watermark algorithm not only eliminate the block effects that might arise in the transform process, but also make full use of Particle Swarm Optimization algorithm to determine the optimal embedding positions and optimal quantization step sizes of the watermark embedding algorithm. It has implemented the adaptive embedding and increased the non-sentience and robustness of the watermark. A series of attacks and comparative experiments show that the performance of the proposed algorithm is better than traditional algorithms.