Quality Scalability Compression on Single-Loop Solution in HEVC

This paper proposes a quality scalable extension design for the upcoming high efficiency video coding (HEVC) standard. In the proposed design, the single-loop decoder solution is extended into the proposed scalable scenario. A novel interlayer intra/interprediction is added to reduce the amount of bits representation by exploiting the correlation between coding layers. The experimental results indicate that the average Bjøntegaard delta rate decrease of 20.50% can be gained compared with the simulcast encoding. The proposed technique achieved 47.98% Bjøntegaard delta rate reduction compared with the scalable video coding extension of the H.264/AVC. Consequently, significant rate savings confirm that the proposed method achieves better performance

A New Transcoding Scheme for Scalable Video Coding to H.264/AVC

Requests from various video terminals push video servers to equip with scalability for video contents distribution in different ways. Scalable Video Coding (SVC) as the extension of H.264/AVC standard can provide the scalability for video servers by encoding videos into one base layer and several enhancement layers. To enable mobile devices without scalability receive videos at their best extent, converting bit-streams from SVC into H.264/AVC becomes the key technique. Bit-stream rewriting is the simplest way without quality loss. However, rewriting is not a real transcoding scheme, since it needs to modify SVC encoders. This paper proposes a novel transcoding approach to support spatial scalability by minimizing the distortions generated from re-encoding process. The proposed scheme keeps the input bit-streams’ information at maximum and adopts the hybrid upsampling method to do residue scaling, which can reduce the transcoding distortion into minimization. Experimental results demonstrate that the loss of the rate-distortion (RD) performance of the proposed transcoding scheme is better than Full Decoding Re-encoding (FDR) which can get the highest video quality in general sense, by achieving up to 0.9 dB Y-PSNR gain while saving 95%~97% processing time

A credit-based approach to scalable video transmission over a peer-to-peer social network

PhDThe objective of the research work presented in this thesis is to study scalable video transmission over peer-to-peer networks. In particular, we analyse how a credit-based approach and exploitation of social networking features can play a significant role in the design of such systems. Peer-to-peer systems are nowadays a valid alternative to the traditional client-server architecture for the distribution of multimedia content, as they transfer the workload from the service provider to the final user, with a subsequent reduction of management costs for the former. On the other hand, scalable video coding helps in dealing with network heterogeneity, since the content can be tailored to the characteristics or resources of the peers. First of all, we present a study that evaluates subjective video quality perceived by the final user under different transmission scenarios. We also propose a video chunk selection algorithm that maximises received video quality under different network conditions. Furthermore, challenges in building reliable peer-to-peer systems for multimedia streaming include optimisation of resource allocation and design mechanisms based on rewards and punishments that provide incentives for users to share their own resources. Our solution relies on a credit-based architecture, where peers do not interact with users that have proven to be malicious in the past. Finally, if peers are allowed to build a social network of trusted users, they can share the local information they have about the network and have a more complete understanding of the type of users they are interacting with. Therefore, in addition to a local credit, a social credit or social reputation is introduced. This thesis concludes with an overview of future developments of this research work