Video transcoding technique is an efficient mechanism to deliver visual contents to a variety of users who have different network conditions or terminal devices with different display capabilities. In this paper, we propose two types of transcoding methods for adapting the bitrate of streaming video to the bandwidth of the transmission channel; spatial resolution reduction (SRR) transcoding and temporal resolution reduction (TRR) transcoding. The two transcoding methods are alternatively operated according to the requirements of users. Experimental results show that the proposed transcoding methods can preserve image quality while transcoding to the low bitrate.

Robustness and invisibility are two contrary constraints for robust invisible watermarking. Instead of the conventional strategy with human visual system (HVS) model, this paper presents a content-adaptive approach to further optimize the constraint between them. To reach this target, the entropy-based and integrated HVS (IHVS) based measures are constructed so as to adaptively choose the suitable components for watermark insertion and detection. Such a kind of scheme potentially gives rise to synchronization problem between the encoder and decoder under the framework of blind watermarking, which is then solved by incorporating the repeat-accumulate (RA) code with erasure and error correction. Moreover, a new hidden Markov model (HMM) based detector in wavelet domain is introduced to reduce the computation complexity and is further developed into a posterior one to avoid the transmission of HMM parameters with only a little sacrifice of detection performance. Experimental results show that the proposed algorithm can obtain considerable improvement in robustness performance with the same distortion as the traditional one.

Video quality generally suffers from packet losses caused by an unreliable channel when video is transmitted over an error-prone wireless channel. This quality degradation is the main reason that a video compression encoder uses error-resilient coding to deal with the high packet-loss probability. The use of adequate error resilience can mitigate the effects of channel errors, but the coding efficiency for bit reduction will be decreased. On the other hand, H.264/AVC uses multiple reference frame (MRF) motion compensation for a higher coding efficiency. However, an increase in the number of reference frames in the H.264/AVC encoder has been recently observed, making the received video quality worse in the presence of transmission errors if the cyclic intra-refresh is used as the error-resilience method. This is because the reference-block selection in the MRF chooses blocks on the basis of the rate distortion optimization, irrespective of the intra-refresh coding. In this paper, a new error-resilient reference selection method is proposed to provide error resilience for MRF based motion compensation. The proposed error-resilient reference selection method achieves an average PSNR enhancement up to 0.5 to 2dB in 10% packet-loss-ratio environments. Therefore, the proposed method can be valuable in most MRF-based interactive video encoding system, which can be used for video broadcasting and mobile video conferencing over an erroneous network.