206 research outputs found

    Applications of sparse approximation in communications

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    Sparse approximation problems abound in many scientific, mathematical, and engineering applications. These problems are defined by two competing notions: we approximate a signal vector as a linear combination of elementary atoms and we require that the approximation be both as accurate and as concise as possible. We introduce two natural and direct applications of these problems and algorithmic solutions in communications. We do so by constructing enhanced codebooks from base codebooks. We show that we can decode these enhanced codebooks in the presence of Gaussian noise. For MIMO wireless communication channels, we construct simultaneous sparse approximation problems and demonstrate that our algorithms can both decode the transmitted signals and estimate the channel parameters

    Efficient compression of motion compensated residuals

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    EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    3D Wavelet Transformation for Visual Data Coding With Spatio and Temporal Scalability as Quality Artifacts: Current State Of The Art

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    Several techniques based on the three–dimensional (3-D) discrete cosine transform (DCT) have been proposed for visual data coding. These techniques fail to provide coding coupled with quality and resolution scalability, which is a significant drawback for contextual domains, such decease diagnosis, satellite image analysis. This paper gives an overview of several state-of-the-art 3-D wavelet coders that do meet these requirements and mainly investigates various types of compression techniques those exists, and putting it all together for a conclusion on further research scope

    Indexing, browsing and searching of digital video

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    Video is a communications medium that normally brings together moving pictures with a synchronised audio track into a discrete piece or pieces of information. The size of a “piece ” of video can variously be referred to as a frame, a shot, a scene, a clip, a programme or an episode, and these are distinguished by their lengths and by their composition. We shall return to the definition of each of these in section 4 this chapter. In modern society, video is ver

    Robust P2P Live Streaming

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    Projecte fet en col.laboració amb la Fundació i2CATThe provisioning of robust real-time communication services (voice, video, etc.) or media contents through the Internet in a distributed manner is an important challenge, which will strongly influence in current and future Internet evolution. Aware of this, we are developing a project named Trilogy leaded by the i2CAT Foundation, which has as main pillar the study, development and evaluation of Peer-to-Peer (P2P) Live streaming architectures for the distribution of high-quality media contents. In this context, this work concretely covers media coding aspects and proposes the use of Multiple Description Coding (MDC) as a flexible solution for providing robust and scalable live streaming over P2P networks. This work describes current state of the art in media coding techniques and P2P streaming architectures, presents the implemented prototype as well as its simulation and validation results

    Frame-based multiple-description video coding with extended orthogonal filter banks

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    We propose a frame-based multiple-description video coder. The analysis filter bank is the extension of an orthogonal filter bank which computes the spatial polyphase components of the original video frames. The output of the filter bank is a set of video sequences which can be compressed with a standard coder. The filter bank design is carried out by taking into account two important requirements for video coding, namely, the fact that the dual synthesis filter bank is FIR, and that loss recovery does not enhance the quantization error. We give explicit results about the required properties of the redundant channel filter and the reconstruction error bounds in case of packet errors. We show that the proposed scheme has good error robustness to losses and good performance, both in terms of objective and visual quality, when compared to single description and other multiple description video coders based on spatial subsampling. PSNR gains of 5 dB or more are typical for packet loss probability as low as 5%

    Source-Channel Diversity for Parallel Channels

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    We consider transmitting a source across a pair of independent, non-ergodic channels with random states (e.g., slow fading channels) so as to minimize the average distortion. The general problem is unsolved. Hence, we focus on comparing two commonly used source and channel encoding systems which correspond to exploiting diversity either at the physical layer through parallel channel coding or at the application layer through multiple description source coding. For on-off channel models, source coding diversity offers better performance. For channels with a continuous range of reception quality, we show the reverse is true. Specifically, we introduce a new figure of merit called the distortion exponent which measures how fast the average distortion decays with SNR. For continuous-state models such as additive white Gaussian noise channels with multiplicative Rayleigh fading, optimal channel coding diversity at the physical layer is more efficient than source coding diversity at the application layer in that the former achieves a better distortion exponent. Finally, we consider a third decoding architecture: multiple description encoding with a joint source-channel decoding. We show that this architecture achieves the same distortion exponent as systems with optimal channel coding diversity for continuous-state channels, and maintains the the advantages of multiple description systems for on-off channels. Thus, the multiple description system with joint decoding achieves the best performance, from among the three architectures considered, on both continuous-state and on-off channels.Comment: 48 pages, 14 figure

    Multiple-Description l1-Compression

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