RBMark: Robust and blind video watermark in DT CWT domain

Video watermark embedding algorithms based on the transform domain are robust against media processing methods but are limited in data embedding capacity. Learning-based watermarking algorithms have recently become increasingly popular because of their good performance in image feature extraction and data embedding. However, they are not consistently robust against various video processing methods. To effectively trade off the embedding capacity and robustness, this paper proposes RBMark, a novel video watermarking method based on Dual-Tree Complex Wavelet Transform (DT CWT). First, the watermark bit-stream is transformed into a key image in the embedding phase. Second, we extract the DT CWT domain coefficients from both the video frame and the key image and embed the key image coefficients into the video frame coefficients. During the extraction phase, the key image coefficients are extracted to perform inverse DT CWT and reconstruct the watermark bit-stream. Compared with prior watermarking algorithms, RBMark achieves higher robustness and embedding capacity. We evaluated its performance using multiple representative video datasets to compare with prior transform domain and learning-based watermarking algorithms. Experimental results demonstrate that RBMark achieves up to 98% and 99% improvement in Bit Error Rate over the transform domain and learning-based methods, respectively. Furthermore, RBMark can embed at most 2040 bits in each 1080p-resolution video frame (i.e., $9.84\times 10^{-4}$ bits per pixel). The source code is available in this URL.