113 research outputs found

    QoS Scalability for Streamed Media Delivery

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    Applications with real-rate progress requirements, such as mediastreaming systems, are difficult to deploy in shared heterogenous environments such as the Internet. On the Internet, mediastreaming systems must be capable of trading off resource requirements against the quality of the media streams they deliver, in order to match wide-ranging dynamic variations in bandwidth between servers and clients. Since quality requirements tend to be user- and task-specific, mechanisms for capturing quality of service requirements and mapping them to appropriate resource-level adaptation policies are required. In this paper, we describe a general approach for automatically mapping user-level quality of service specifications onto resource consumption scaling policies. Quality of service specifications are given through utility functions, and priority packet dropping for layered media streams is the resource scaling technique. The approach emphasizes simple mechanisms, yet facilitates fine-grained policy-driven adaptation over a wide-range of bandwidth levels. We demonstrate the approach in a streamingvideo player that supports user-tailorable quality adaptation policies both for matching its resource consumption requirements to the capabilities of heterogeneous clients, and for responding to dynamic variations in system and network load

    Resource-Constrained Low-Complexity Video Coding for Wireless Transmission

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    Compressed-domain transcoding of H.264/AVC and SVC video streams

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    Scalable and perceptual audio compression

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    This thesis deals with scalable perceptual audio compression. Two scalable perceptual solutions as well as a scalable to lossless solution are proposed and investigated. One of the scalable perceptual solutions is built around sinusoidal modelling of the audio signal whilst the other is built on a transform coding paradigm. The scalable coders are shown to scale both in a waveform matching manner as well as a psychoacoustic manner. In order to measure the psychoacoustic scalability of the systems investigated in this thesis, the similarity between the original signal\u27s psychoacoustic parameters and that of the synthesized signal are compared. The psychoacoustic parameters used are loudness, sharpness, tonahty and roughness. This analysis technique is a novel method used in this thesis and it allows an insight into the perceptual distortion that has been introduced by any coder analyzed in this manner

    Quality assessment of multidimensional video scalability

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    Scalability is a powerful concept for adaptive video content delivery to many end users having heterogeneous and dynamic characteristics of networks and devices. In order to maximize users' quality of experience by selecting appropriate combinations of multiple scalability parameters, it is crucial to understand and model the relationship between multidimensional scalability and perceived quality. In this article, we address the latest advances in subjective and objective quality evaluation of multidimensional video scalability for optimal content distribution, present their applications, and discuss future trends and challenges

    Rate Control in Video Coding

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    Scalable coding of HDTV pictures using the MPEG coder

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    Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (leaves 118-121).by Adnan Husain Lawai.M.S

    A rate control algorithm for scalable video coding

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    This thesis proposes a rate control (RC) algorithm for H.264/scalable video coding (SVC) specially designed for real-time variable bit rate (VBR) applications with buffer constraints. The VBR controller assumes that consecutive pictures within the same scene often exhibit similar degrees of complexity, and aims to prevent unnecessary quantization parameter (QP) fluctuations by allowing for just an incremental variation of QP with respect to that of the previous picture. In order to adapt this idea to H.264/SVC, a rate controller is located at each dependency layer (spatial or coarse grain scalability) so that each rate controller is responsible for determining the proper QP increment. Actually, one of the main contributions of the thesis is a QP increment regression model that is based on Gaussian processes. This model has been derived from some observations drawn from a discrete set of representative encoding states. Two real-time application scenarios were simulated to assess the performance of the VBR controller with respect to two well-known RC methods. The experimental results show that our proposal achieves an excellent performance in terms of quality consistency, buffer control, adjustment to the target bit rate, and computational complexity. Moreover, unlike typical RC algorithms for SVC that only satisfy the hypothetical reference decoder (HRD) constraints for the highest temporal resolution sub-stream of each dependency layer, the proposed VBR controller also delivers HRD-compliant sub-streams with lower temporal resolutions.To this end, a novel approach that uses a set of buffers (one per temporal resolution sub-stream) within a dependency layer has been built on top of the RC algorithm.The proposed approach aims to simultaneously control the buffer levels for overflow and underflow prevention, while maximizing the reconstructed video quality of the corresponding sub-streams. This in-layer multibuffer framework for rate-controlled SVC does not require additional dependency layers to deliver different HRD-compliant temporal resolutions for a given video source, thus improving the coding e ciency when compared to typical SVC encoder con gurations since, for the same target bit rate, less layers are encoded
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