Interframe and interview predictions are widely employed in multiview video coding. This technique improves the coding efficiency, but it also increases the vulnerability of the coded bitstream. Thus, one packet loss ...
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Interframe and interview predictions are widely employed in multiview video coding. This technique improves the coding efficiency, but it also increases the vulnerability of the coded bitstream. Thus, one packet loss will affect many subsequent frames in the same view and probably in other referenced views. To address this problem, a region-based multiple description coding scheme is proposed for robust 3-D video communication in this paper, in which two descriptions are formed by setting the left and right view as dominant in the first and second description, respectively. This approach exploits the fact that most regions in the reference view could be synthesized from the base view. Hence, these regions could be skipped or only coarsely encoded. In our work, the disoccluded regions, illumination-affected regions, and remaining regions are first determined and extracted. By assigning different quantization parameters for these three different regions according to the network status, an efficient multipledescription scheme is formed. Experimental results demonstrate that the proposed scheme achieves considerably better performance compared with the traditional approach.
In this paper, a prediction-compensated multipledescription (MD) coding framework for two-band filter banks is proposed, in which the coefficients in each subband are split into two descriptions. Each description als...
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In this paper, a prediction-compensated multipledescription (MD) coding framework for two-band filter banks is proposed, in which the coefficients in each subband are split into two descriptions. Each description also includes the prediction residuals of the data in the other description. The designs of the optimal orthogonal and biorthogonal filter banks are formulated in a unified framework, and both one-level and multiple-level decompositions are analyzed. Contrary to the existing MD filter banks in the literature, the optimal filter banks in the proposed scheme are quite similar to those in single descriptioncoding. Therefore, the method can be applied to systems with single-description-optimized filter banks and still attain near-optimal performance. Image coding results show that this method achieves better performance and lower complexity than the latest JPEG 2000 based MDC.
This paper examines the effectiveness of combining multiple description coding (MDC) and multiple path transport (MPT) for video and image transmission in a multihop mobile radio network. The video and image informati...
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This paper examines the effectiveness of combining multiple description coding (MDC) and multiple path transport (MPT) for video and image transmission in a multihop mobile radio network. The video and image information is encoded nonhierarchically into multipledescriptions with the following objectives. The received picture quality should be acceptable, even if only one description is received and every additional received description contributes to enhanced picture quality. Typical applications will need a higher bandwidth/higher reliability connection than that provided by a single link in current mobile networks. For supporting these, applications, a mobile node may need to set up and use multiple paths to the desired destination, either simply because of the lack of raw bandwidth on a single channel or because of its poor error characteristics, which reduce its effective throughput. In the context of this work, the principal reasons for considering such an architecture are providing high bandwidth and more robust end-to-end connections. We describe a protocol architecture that addresses this need and, with the help of simulations, we demonstrate the feasibility of this system and compare the performance of the MDC-MPT scheme to a system using layered coding and asymmetrical paths for the base and enhancement layers.
multiple description coding (MDC) is an error-resilient source coding scheme that creates multiple bitstreams of approximately equal importance. The reconstructed signal based on any single bitstream has an acceptable...
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multiple description coding (MDC) is an error-resilient source coding scheme that creates multiple bitstreams of approximately equal importance. The reconstructed signal based on any single bitstream has an acceptable quality. However, a higher quality reconstruction can be achieved with a larger number of bitstreams. We develop a multiple (2) description video coding scheme based on the three-loop structure originally proposed in [1]. We modify the discrete cosine transform structure to the matching pursuits framework and evaluate performance gain using maximum-likelihood (ML) enhancement when both descriptions are available. We find that ML enhancement works best for low motion sequences and results in gains of up to 1.3 dB in terms of average PSNR. Rate distortion performance is characterized. Performance comparison is made between our MDC scheme and single descriptioncoding (SDC) schemes over lossy channels, including two state Markov channels and Rayleigh fading channels. We find that MDC outperforms SDC in bursty slowly varying environments. In the case of Rayleigh fading channels, interleaving helps SDC close the gap and even outperform MDC depending on the amount of interleaving performed, at the expense of additional delay.
Compressed sensing (CS) is an emerging paradigm for acquisition of compressed representations of a sparse signal. Its low complexity is appealing for resource-constrained scenarios like sensor networks. However, such ...
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Compressed sensing (CS) is an emerging paradigm for acquisition of compressed representations of a sparse signal. Its low complexity is appealing for resource-constrained scenarios like sensor networks. However, such scenarios are often coupled with unreliable communication channels and providing robust transmission of the acquired data to a receiver is an issue. multiple description coding (MDC) effectively combats channel losses for systems without feedback, thus raising the interest in developing MDC methods explicitly designed for the CS framework, and exploiting its properties. We propose a method called Graded Quantization (CS-GQ) that leverages the democratic property of compressive measurements to effectively implement MDC, and we provide methods to optimize its performance. A novel decoding algorithm based on the alternating directions method of multipliers is derived to reconstruct signals from a limited number of received descriptions. Simulations are performed to assess the performance of CS-GQ against other methods in presence of packet losses. The proposed method is successful at providing robust coding of CS measurements and outperforms other schemes for the considered test metrics.
This paper examines the use of multiple description coding (MDC) for information transmission over multiple correlated erasure channels. It addresses the problem of optimal rate allocation between descriptions to atta...
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This paper examines the use of multiple description coding (MDC) for information transmission over multiple correlated erasure channels. It addresses the problem of optimal rate allocation between descriptions to attain the minimum possible average distortion at the receiver. The rate allocation problem is formulated on the basis of rate-distortion theory for the general case of unbalanced MDC and under the constraint that the total coding rate is fixed. The channel parameters, that is, erasure rates, for which MDC outperforms Single descriptioncoding are characterised. It is shown that MDC is optimal when the channel erasure rates are comparable and the total coding rate is large. A heuristic approximation for optimal rate allocation is also presented, which can be readily used in practice to determine the relative rates between descriptions needed to achieve the minimal average distortion. The relationship between the optimal average distortion and the erasure correlation is explored. It is shown that for some cases, such as for equal average erasure probabilities, the average distortion decreases as the channel correlation increases. Copyright (c) 2012 John Wiley & Sons, Ltd.
Ghost imaging (GI) reveals its exceptional superiority over conventional cameras in a range of challenging scenarios such as weak illumination or special waveband. For high-performance GI, it is vital to obtain a sequ...
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Ghost imaging (GI) reveals its exceptional superiority over conventional cameras in a range of challenging scenarios such as weak illumination or special waveband. For high-performance GI, it is vital to obtain a sequence of high-fidelity bucket signals. However, measurements may suffer from distortion or loss in harsh environments. Here we present multiple description coding ghost imaging, which rests on illumination consisting of different coding patterns to address this challenge. Experimental results indicate that the proposed method is capable of producing satisfactory image even when the sequence of bucket signals is incomplete or highly distorted. This method provides an encouraging boost for GI in practical applications.
3D video is becoming a most favorable video and attracting researcher's mind to provide robust methods of streaming since packet failure has always been the inseparable characteristic of wired or wireless networks...
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ISBN:
(纸本)9789897582257
3D video is becoming a most favorable video and attracting researcher's mind to provide robust methods of streaming since packet failure has always been the inseparable characteristic of wired or wireless networks. This paper aims to provide a new multiple description coding for 3D video considering objects existed in the scene. To this end, a low complex algorithm for realizing objects in 3D scene will provided and then a nonidentical decimation method with respect to objects will be utilized to produce descriptions of MDC approach. Also, in point of depth map image, a new non-identical MDC algorithm will be be introduced to stream depth map image saving bandwidth without affecting the quality of decoded video in the receiver side.
One of the important issues in multiple description coding (MDC) for image and video signals is to compose pictures of the "best" quality when more than one description is received at the decoder side. To th...
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ISBN:
(纸本)9780819482341
One of the important issues in multiple description coding (MDC) for image and video signals is to compose pictures of the "best" quality when more than one description is received at the decoder side. To this goal, a transform-domain overlapping technique combined with some necessary translations in the transform domain is proposed in the popular MDC schemes with staggered quantizers. However, the achievable gain is rather limited. In this paper, we formulate this enhancement problem as a total variation (TV) regularized optimization constrained by the knowledge of the quantization intervals of the DCT coefficients of each composed picture. In this TV-based approach, the transform-domain overlapping technique is used to find the more accurate quantization intervals in which the true DCT coefficients will fall while receiving more than one description. Simulation results demonstrate that such a TV-based enhancement yields a higher quality gain in both objective (e.g. PSNR-based) and subjective (i.e. visual perception) evaluations than using the transform-domain overlapping technique.
We derive a single-letter lower bound on the minimum sum rate of multiple description coding with symmetric distortion constraints. For the binary uniform source with the erasure distortion measure or Hamming distorti...
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We derive a single-letter lower bound on the minimum sum rate of multiple description coding with symmetric distortion constraints. For the binary uniform source with the erasure distortion measure or Hamming distortion measure, this lower bound can be evaluated with the aid of certain minimax theorems. A similar minimax theorem is established in the quadratic Gaussian setting, which is further leveraged to analyze the special case where the minimum sum rate subject to two levels of distortion constraints (with the second level imposed on the complete set of descriptions) is attained;in particular, we determine the minimum achievable distortions at the intermediate levels.
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