2,365 research outputs found

    Slice group based multiple description video coding using motion vector estimation

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    Resilient Digital Video Transmission over Wireless Channels using Pixel-Level Artefact Detection Mechanisms

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    Recent advances in communications and video coding technology have brought multimedia communications into everyday life, where a variety of services and applications are being integrated within different devices such that multimedia content is provided everywhere and on any device. H.264/AVC provides a major advance on preceding video coding standards obtaining as much as twice the coding efficiency over these standards (Richardson I.E.G., 2003, Wiegand T. & Sullivan G.J., 2007). Furthermore, this new codec inserts video related information within network abstraction layer units (NALUs), which facilitates the transmission of H.264/AVC coded sequences over a variety of network environments (Stockhammer, T. & Hannuksela M.M., 2005) making it applicable for a broad range of applications such as TV broadcasting, mobile TV, video-on-demand, digital media storage, high definition TV, multimedia streaming and conversational applications. Real-time wireless conversational and broadcast applications are particularly challenging as, in general, reliable delivery cannot be guaranteed (Stockhammer, T. & Hannuksela M.M., 2005). The H.264/AVC standard specifies several error resilient strategies to minimise the effect of transmission errors on the perceptual quality of the reconstructed video sequences. However, these methods assume a packet-loss scenario where the receiver discards and conceals all the video information contained within a corrupted NALU packet. This implies that the error resilient methods adopted by the standard operate at a lower bound since not all the information contained within a corrupted NALU packet is un-utilizable (Stockhammer, T. et al., 2003).peer-reviewe

    Multiple description video coding for real-time applications using HEVC

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    Remote control vehicles require the transmission of large amounts of data, and video is one of the most important sources for the driver. To ensure reliable video transmission, the encoded video stream is transmitted simultaneously over multiple channels. However, this solution incurs a high transmission cost due to the wireless channel's unreliable and random bit loss characteristics. To address this issue, it is necessary to use more efficient video encoding methods that can make the video stream robust to noise. In this paper, we propose a low-complexity, low-latency 2-channel Multiple Description Coding (MDC) solution with an adaptive Instantaneous Decoder Refresh (IDR) frame period, which is compatible with the HEVC standard. This method shows better resistance to high packet loss rates with lower complexity

    Error resilience and concealment techniques for high-efficiency video coding

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    This thesis investigates the problem of robust coding and error concealment in High Efficiency Video Coding (HEVC). After a review of the current state of the art, a simulation study about error robustness, revealed that the HEVC has weak protection against network losses with significant impact on video quality degradation. Based on this evidence, the first contribution of this work is a new method to reduce the temporal dependencies between motion vectors, by improving the decoded video quality without compromising the compression efficiency. The second contribution of this thesis is a two-stage approach for reducing the mismatch of temporal predictions in case of video streams received with errors or lost data. At the encoding stage, the reference pictures are dynamically distributed based on a constrained Lagrangian rate-distortion optimization to reduce the number of predictions from a single reference. At the streaming stage, a prioritization algorithm, based on spatial dependencies, selects a reduced set of motion vectors to be transmitted, as side information, to reduce mismatched motion predictions at the decoder. The problem of error concealment-aware video coding is also investigated to enhance the overall error robustness. A new approach based on scalable coding and optimally error concealment selection is proposed, where the optimal error concealment modes are found by simulating transmission losses, followed by a saliency-weighted optimisation. Moreover, recovery residual information is encoded using a rate-controlled enhancement layer. Both are transmitted to the decoder to be used in case of data loss. Finally, an adaptive error resilience scheme is proposed to dynamically predict the video stream that achieves the highest decoded quality for a particular loss case. A neural network selects among the various video streams, encoded with different levels of compression efficiency and error protection, based on information from the video signal, the coded stream and the transmission network. Overall, the new robust video coding methods investigated in this thesis yield consistent quality gains in comparison with other existing methods and also the ones implemented in the HEVC reference software. Furthermore, the trade-off between coding efficiency and error robustness is also better in the proposed methods
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