183 research outputs found

    Rate Control for VBR Video Coders in Broadband Networks

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    Predictive Encoder and Buffer Control for Statistical Multiplexing of Multimedia Contents

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    International audienceStatistical multiplexing of video contents aims at transmitting several variable bit rate (VBR) encoded video streams over a band-limited channel. Rate-distortion (RD) models for the encoded streams are often used to control the video encoders. Buffering at the output of encoders is one of the several techniques used to smooth out the fluctuating bit rate of compressed video due to variations in the activity of video contents. In this paper, a statistical multiplexer is proposed where a closed-loop control of both video encoders and buffers is performed jointly. First, a predictive joint video encoder controller accounting for minimum quality, fairness, and smoothness constraints is considered. Second, all buffers are controlled simultaneously to regulate the buffering delays. This delay is adjusted according to a reference delay constraint. The main idea is to update the encoding rate for each video unit according to the average level of the buffers, to maximize the quality of each program and effectively use the available channel rate. Simulation results show that the proposed scheme yields a smooth and fair video quality among programs thanks to the predictive control. A similar buffering delay for all programs and an efficient use of the available channel rate are ensured thanks to the buffer management and to the predictive closed-loop control

    MASCOT : metadata for advanced scalable video coding tools : final report

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    The goal of the MASCOT project was to develop new video coding schemes and tools that provide both an increased coding efficiency as well as extended scalability features compared to technology that was available at the beginning of the project. Towards that goal the following tools would be used: - metadata-based coding tools; - new spatiotemporal decompositions; - new prediction schemes. Although the initial goal was to develop one single codec architecture that was able to combine all new coding tools that were foreseen when the project was formulated, it became clear that this would limit the selection of the new tools. Therefore the consortium decided to develop two codec frameworks within the project, a standard hybrid DCT-based codec and a 3D wavelet-based codec, which together are able to accommodate all tools developed during the course of the project

    Flow control of real-time unicast multimedia applications in best-effort networks

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    One of the fastest growing segments of Internet applications are real-time mul- timedia applications, like Voice over Internet Protocol (VoIP). Real-time multimedia applications use the User Datagram Protocol (UDP) as the transport protocol because of the inherent conservative nature of the congestion avoidance schemes of Transmis- sion Control Protocol (TCP). The e®ects of uncontrolled °ows on the Internet have not yet been felt because UDP tra±c frequently constitutes only » 20% of the total Internet tra±c. It is pertinent that real-time multimedia applications become better citizens of the Internet, while at the same time deliver acceptable Quality of Service (QoS). Traditionally, packet losses and the increase in the end-to-end delay experienced by some of the packets characterizes congestion in the network. These two signals have been used to develop most known °ow control schemes. The current research considers the °ow accumulation in the network as the signal for use in °ow control. The most signi¯cant contribution of the current research is to propose novel end- to-end °ow control schemes for unicast real-time multimedia °ows transmitting over best-e®ort networks. These control schemes are based on predictive control of the accumulation signal. The end-to-end control schemes available in the literature are based on reactive control that do not take into account the feedback delay existing between the sender and the receiver nor the forward delay in the °ow dynamics. The performance of the proposed control schemes has been evaluated using the ns-2 simulation environment. The research concludes that active control of hard real- time °ows delivers the same or somewhat better QoS as High Bit Rate (HBR, no control), but with a lower average bit rate. Consequently, it helps reduce bandwidth use of controlled real-time °ows by anywhere between 31:43% to 43:96%. Proposed reactive control schemes deliver good QoS. However, they do not scale up as well as the predictive control schemes. Proposed predictive control schemes are e®ective in delivering good quality QoS while using up less bandwidth than even the reactive con- trol schemes. They scale up well as more real-time multimedia °ows start employing them

    Analog parallel processor solutions for video encoding

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    This thesis deals with Cellular Nonlinear Network (CNN) analog parallel processor networks and their implementations in current video coding standards. The target applications are low-power video encoders within 3rd generation mobile terminals. The video codecs of such mobile terminals are defined by either the MPEG-4/H.263 or H.264 video standard. All of these standards are based on the block-based hybrid approach. As block-based motion estimation (ME) is responsible for most of the power consumption of such hybrid video encoders, this thesis deals mostly with low-power ME implementations. Low-power solutions are introduced at both the algorithmic and hardware levels. On the algorithmic level, the introduced implementations are derived from a segmentation algorithm, which has previously been partly realized. The first introduced algorithm reduces the computational complexity of ME within an object-based MPEG-4 encoder. The use of this algorithm enables a 60% drop in the power consumption of Full Search ME. The second algorithm calculates a near-optimal block-size partition for H.264 motion estimation. With this algorithm, the use of computationally complex Lagrange optimization in H.264 ME is not required. The third algorithm reduces the shape bit-rate of an object-based MPEG-4 encoder. On the hardware level a CNN-type ME architecture is introduced. The architecture includes connections and circuitry to fully realize block-based ME. The analog ME implemented with this architecture is capable of lower power than comparable digital realizations. A 9×9 test chip has also been realized. Additionally implemented is a digital predictive ME realization that takes advantage of the introduced partition algorithm. Although the IC layout of the ME algorithm was drawn, the design was verified as an FPGA.reviewe

    Rate-distortion analysis and traffic modeling of scalable video coders

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    In this work, we focus on two important goals of the transmission of scalable video over the Internet. The first goal is to provide high quality video to end users and the second one is to properly design networks and predict network performance for video transmission based on the characteristics of existing video traffic. Rate-distortion (R-D) based schemes are often applied to improve and stabilize video quality; however, the lack of R-D modeling of scalable coders limits their applications in scalable streaming. Thus, in the first part of this work, we analyze R-D curves of scalable video coders and propose a novel operational R-D model. We evaluate and demonstrate the accuracy of our R-D function in various scalable coders, such as Fine Granular Scalable (FGS) and Progressive FGS coders. Furthermore, due to the time-constraint nature of Internet streaming, we propose another operational R-D model, which is accurate yet with low computational cost, and apply it to streaming applications for quality control purposes. The Internet is a changing environment; however, most quality control approaches only consider constant bit rate (CBR) channels and no specific studies have been conducted for quality control in variable bit rate (VBR) channels. To fill this void, we examine an asymptotically stable congestion control mechanism and combine it with our R-D model to present smooth visual quality to end users under various network conditions. Our second focus in this work concerns the modeling and analysis of video traffic, which is crucial to protocol design and efficient network utilization for video transmission. Although scalable video traffic is expected to be an important source for the Internet, we find that little work has been done on analyzing or modeling it. In this regard, we develop a frame-level hybrid framework for modeling multi-layer VBR video traffic. In the proposed framework, the base layer is modeled using a combination of wavelet and time-domain methods and the enhancement layer is linearly predicted from the base layer using the cross-layer correlation

    Rate Control in Video Coding

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