1,721,093 research outputs found
A Linear Time-Varying Approach to the Problem of Signal Reconstruction from a Finite Set of Irregularly Spaced Noisy Samples
No full textMultiple Description Distributed Video Coding Using Redundant Slices and Lossy Syndromes
No full textDuring the last years, video coding designers have proposed robust coding approaches that combine Multiple Description Coding (MDC) schemes with Distributed Video Coding (DVC) principles. In this way, it is possible to obtain a better error resilience since the distortion drifting through the sequence is significantly mitigated by the DVC coding unit. The paper presents a Multiple Description Distributed Video Coder (MDDVC) that codes the input video signal generating a set of "lossy" syndromes for each pixel block and creates different descriptions multiplexing primary and redundant video packets. Experimental results show that at high loss probabilities the proposed solution improves the results of the original MDC approach
Lossless Compression of Color Sequences Using Optimal Linear Prediction Theory
No full textIn this paper, we present a novel technique that uses the optimal linear prediction theory to exploit all the existing redundancies in a color video sequence for lossless compression purposes. The main idea is to introduce the spatial, the spectral, and the temporal correlations in the autocorrelation matrix estimate. In this way, we calculate the cross correlations between adjacent frames and adjacent color components to improve the prediction, i.e., reduce the prediction error energy. The residual image is then coded using a context-based Golomb-Rice coder, where the error modeling is provided by a quantized version of the local prediction error variance. Experimental results show that the proposed algorithm achieves good compression ratios and it is roboust against the scene change problem
A Low-Complexity Cross-Layer Optimization Algorithm for Video Communication Over Wireless Networks
No full textRecent years have witnessed a rapid increment in video applications over wireless networks including on-demand video streaming and videophoning. This growth has also brought the need to find a good compromise in the conflict between resource limitations affecting mobile devices and the desire for high-quality multimedia services. It is possible to face this problem adopting a cross-layer strategy that jointly tunes the parameters of each layer in the network protocol stack. In this optimization strategy, complexity is one of the most significant issues because of the limited computational resources and power supply. The paper presents a low-complexity cross-layer algorithm that is able to jointly tune the parameters of different protocol layers by adopting simple but effective models. The quality of the reconstructed video sequence, the produced bit rate, and the service class associated to each packet are seen as functions of the percentage of null DCT coefficients. This modeling permits to find a closed-form solution to the joint optimization problem that can be computed with a limited number of operations and grants, at the same time, a good visual quality in the reconstructed sequence
Distributed video coding based on lossy syndromes generated in hybrid pixel/transform domain
No full textA Distributed Video Coding Approach for Multiple Description Video Coding of Stereo Sequences
No full textA Low-Complexity Rate Allocation Algorithm for Joint Source-Channel Video Coding
No full textThe problem of enabling robust video transmission over lossy networks has become increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks. The more the coding process relies on an intensive use of prediction to improve the coding gain, the more the reconstructed sequence proves to be sensitive to information losses. As a matter of fact, it is necessary to introduce some redundant data in order to increase the robustness of the coded bit stream. A possible solution can be found filling a matrix structure with RTP packets and applying a Forward Error Correction (FEC) code on its rows. However, the matrix size and the chosen FEC code affect the performance of the coding system. The paper proposes a novel adaptation technique that tunes the amount of redundant information included in the packet stream and differs from previously proposed solutions since it relies on the percentage of null quantized transform coefficients in place of the activity or the Mean Square Error (MSE). This strategy is then integrated in a joint source-channel coder rate allocation algorithm that shares the available bits between the H.264/AVC coder and the channel coder according to the significance of the frame in the decoding process. Experimental results show that the presented approach significantly improves the quality of the reconstructed sequences at the decoder with respect to activity-based strategies and requires a low computational complexity. (C) 2009 Elsevier B.V. All rights reserved
On the realization of minimum noise and low-noise frequency sampling FIR filters
No full textIn this work the finite precision effects issue connected to the frequency sampling realization of FIR filters is considered. In particular, the performance of the frequency sampling filters is evaluated in terms of noise gain for the following three different realizations of the second-order elementary sections: the canonical direct form, the minimum roundoff noise structure, and the suboptimal state-space structure introduced by Bomar. An interesting property on the design of minimum noise second-order sections embedded in the frequency sampling structure, is given. The results obtained show that the realizations via minimum noise structures and Bomar's structures greatly outperform the realizations via canonical direct form structures, and, for very narrow-band filters, have noise gain comparable to that of nonrecursive direct realization
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