Transmission of video over bandwidth varying networks like the Internet requires a highly scalable solution capable of adapting to the network condition in real-time. To address this requirement, scalable video-coding...
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Transmission of video over bandwidth varying networks like the Internet requires a highly scalable solution capable of adapting to the network condition in real-time. To address this requirement, scalable video-coding schemes with multiple enhancement layers have been proposed. However, under this multiple-layer paradigm, the transmission bit-rate of each layer has to be predetermined at encoding time. Consequently, the range of bit-rates that can be covered with these compression schemes is limited and often lower than, or different from, the desired range required at transmission time. In this paper, a novel scalable video-coding framework and a corresponding compression method for Internet video streaming are introduced. Building upon the MPEG-4 SNR fine-granular-scalability (FGS) approach, the proposed framework provides a new level of abstraction between the encoding and transmission process by supporting both SNR and temporal scalability through a single enhancement layer. Therefore, our proposed approach enables streaming systems to support full SNR, full temporal, and hybrid temporal-SNR scalability in real-time depending on the available bandwidth, packet-loss patterns, user preferences, and/or receiver complexity. Moreover, our experiments revealed that the presented FGS temporal-SNR scalability has similar or better PSNR performance than the multilayer scalability schemes. Subsequently, an Internet video streaming system employing the proposed hybrid FGS-temporal scalability structure is introduced, together with a very simple, yet effective, rate-control that performs the tradeoffs between individual image quality (SNR) and motion-smoothness in real-time. The hybrid temporal-SNR scalability presented in this paper has been recently adopted in the MPEG-4 standard to support video-streaming applications.
Computer networks and the internet have taken an important role in modern society. Together with their development, the need for digital video transmission over these networks has grown. To cope with the user demands ...
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ISBN:
(纸本)0819454966
Computer networks and the internet have taken an important role in modern society. Together with their development, the need for digital video transmission over these networks has grown. To cope with the user demands and limitations of the network, compression of the video material has become an important issue. Additionally, many video-applications require flexibility in terms of scalability and complexity (e.g. HD/SD-TV, video-surveillance). Current ITU-T and ISO/IEC video compression standards (MPEG-x, H.26-x) lack efficient support for these types of scalability. Wavelet-based compression techniques have been proposed to tackle this problem, of which the Motion Compensated Temporal Filtering (MCTF)-based architectures couple state-of-the-art performance with full (quality, resolution, and frame-rate) scalability. However, a significant drawback of these architectures is their high complexity. The computational and memory complexity of both spatial domain (SD) MCTF and in-band (IB) MCTF video codec instantiations are examined in this study. Comparisons in terms of complexity versus performance are presented for both types of codecs. The paper indicates how complexity scalability can be achieved in such video-codecs, and analyses some of the trade-offs between complexity and coding performance. Finally, guidelines on how to implement a fully scalablevideo-codec that incorporates quality, temporal, resolution and complexity scalability are proposed.
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