A novel watermarking framework for scalable coded video that improves the robustness against quality scalable compression is presented in this paper. Unlike the conventional spatial-domain (t？+？2D) water-marking scheme where the motion compensated temporal filtering (MCTF) is performed on the spatial frame-wise video data to decompose the video, the proposed framework applies the MCTF in the wavelet domain (2D？+？t) to generate the coefficients to embed the watermark. Robustness performances against scalable content adaptation, such as Motion JPEG 2000, MC-EZBC, or H.264-SVC, are reviewed for various combinations of motion compensated 2D？+？t？+？2D using the proposed framework. The MCTF is improved by modifying the update step to follow the motion trajectory in the hierarchical temporal decomposition by using direct motion vector fields in the update step and implied motion vectors in the prediction step. The results show smaller embedding distortion in terms of both peak signal to noise ratio and flickering metrics compared to frame-by-frame video watermarking while the robustness against scalable compression is improved by using 2D？+？t over the conventional t？+？2D domain video watermarking, particularly for blind watermarking schemes where the motion is estimated from the watermarked video. 1. Introduction Several attempts have been made to extend the image watermarking algorithms into video watermarking by using them either on frame-by-frame basis or on 3D decomposed video. The initial attempts on video watermarking were made by frame-by-frame embedding [1–4], due to its simplicity in implementation using image watermarking algorithms. Such watermarking algorithms consider embedding on selected frames located at fixed intervals to make them robust against frame dropping-based temporal adaptations of video. In this case, each frame is treated separately as an individual image; hence, any image-watermarking algorithm can be adopted to achieve the intended robustness. But frame-by-frame watermarking schemes often perform poorly in terms of flickering artefacts and robustness against various video processing attacks including temporal desynchronization, video collusion, video compression attacks, and so forth. In order to address some of these issues, the video temporal dimension is exploited using different transforms, such as discrete Fourier transform (DFT), discrete cosine transform (DCT), or discrete wavelet transform (DWT). These algorithms decompose the video by performing spatial 2D transform on individual frames followed by 1D transform in the
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