Geometrical attacks can destroy most watermarking systems at present. So how to efficiently resist such kind of attacks remains a challenging direction in water- marking research. In this paper, a novel sequence watermarking scheme, which exploits a geometrical invariant, i.e. average AC energy (AAE) to combat arbitrary geometrical at- tacks, is presented. The scheme also uses some other measures, such as synchroniza- tion and optimal whitening filter to resist other attacks and improve detection performance. The experimental results show that the scheme can efficiently improve the visual quality of the watermarked video and achieve good robustness against random geometrical attacks. The scheme also has good robustness against other attacks, such as low-pass filtering along time axis and frame removal.
Distributed video coding (DVC) arouses high interests due to its property of low-complexity encoding. This paper proposes a robust multiple description DVC (MDDVC) under the constraint of low-complexity encoding. In MDDVC,zeros are padded to each frame and the resulting big-size video is divided into multiple descriptions. Then,each description is compressed by a hybrid DVC (HDVC) codec and trans-mitted over different channel. When one channel does not work,the lost HDVC description is estimated by the received from other channel,which guarantees the robustness of the system;MDDVC moves the complex motion estimation totally to the decoder so it features low-complexity encoding. In the pre-processing,an optimized zero-padding is also proposed to improve the performance. Experimen-tal results exhibit that the proposed MDDVC scheme achieves better rate-distortion performance and robustness than the referenced especially when packet-loss rate is high.
A novel lossless data hiding scheme based on a combination of prediction and the prediction-error adjustment (PEA) is presented in this paper. For one pixel,its four surrounding neighboring pixels are used to predict it and 1-bit watermark information is embedded into the prediction-error. In traditional approaches,for the purpose of controlling embedding distortion,only pixels with small prediction-errors are used for embedding. However,when the threshold is small,it is difficult to efficiently com-press the location map which is used to identify embedding locations. Thus,PEA is introduced to make large prediction-error available for embedding while causing low embedding distortions,and accord-ingly,the location map can be compressed well. As a result,the hiding capacity is largely increased. A series of experiments are conducted to verify the effectiveness and advantages of the proposed ap-proach.
Nowadays,distributed source coding(DSC)and distributed video coding(DVC)have been receiving more and more attention due to the distinct contributions to the easy encoding.At the same time,with more new requirements coming forth in the current network communication,the scalability of bit stream has been a new focus in the real applications.A scalable DVC scheme is presented without requiring layered coding in which the main attributions of DVC,namely the capabilities of easy encoding and robustness, are inherited remarkably and the property of scalability is also integrated simultaneously.Based on the block Slepian-Wolf set partitioning in hierarchical trees(SW-SPIHT),the Wyner-Ziv frames are encoded to get the scalable bit stream.In addition,the binary motion searching is explored at the decoder with the help of a rate-variable‘hash’from the encoder to improve the performance of the whole system.The final experimental results show that our system has higher peak signal-to-noise ratio(PSNR)than the pixel-domain DVC at the high bit rate.What is more,the scalability in signal-to-noise ratio(SNR)is also achieved satisfactorily.
