Traditional video servers partially cope with heterogeneous client populations by maintaining a few versions of the same stream with different bit rates. More recent video servers leverage multilayer scalable coding t...
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Traditional video servers partially cope with heterogeneous client populations by maintaining a few versions of the same stream with different bit rates. More recent video servers leverage multilayer scalable coding techniques to customize the quality for individual clients. In both cases, heuristic, error-prone, techniques are currently used by administrators to determine either the rate of each stream version, or the granularity and rate of each layer in a multilayer scalable stream. In this paper, we propose an algorithm to determine the optimal rate and encoding granularity of each layer in a scalable video stream that maximizes a system-defined utility function for a given client distribution. The proposed algorithm can be used to compute the optimal rates of multiversion streams as well. Our algorithm is general in the sense that it can employ arbitrary utility functions for clients. We implement our algorithm and verify its optimality, and we show how various structuring of scalable video streams affect the client utilities. To demonstrate the generality of our algorithm, we consider three utility functions in our experiments. These utility functions model various aspects of streaming systems, including the effective rate received by clients, the mismatch between client bandwidth and received stream rate, and the client-perceived quality in terms of PSNR. We compare our algorithm against a heuristic algorithm that has been used before in the literature, and we show that our algorithm outperforms it in all cases.
We consider the transmission of a Gaussian source through a block fading channel. Assuming each block is decoded independently, the received distortion depends on the trade-off between quantization accuracy and probab...
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We consider the transmission of a Gaussian source through a block fading channel. Assuming each block is decoded independently, the received distortion depends on the trade-off between quantization accuracy and probability of outage. Namely higher quantization accuracy requires a higher. channel code rate, which increases the probability of outage. We first treat an outage as an erasure, and evaluate the received mean distortion with erasure coding across blocks as a function of the code length. We then evaluate the performance of scalable, or multi-resolution coding in which coded layers are superimposed within a coherence block, and-the layers are sequentially decoded. Both the rate and power allocated to each layer are optimized. In addition to analyzing the performance with a finite number of layers, we evaluate the mean distortion at high Signal-to-Noise Ratios as the number of layers becomes infinite. As the block length of the erasure code increases to infinity, the received distortion converges to a deterministic limit, which is less than the mean distortion with an infinite-layer scalable coding scheme. However, for the same standard deviation in received distortion, infinite layer scalable coding performs slightly better than erasure coding, and with much less decoding delay.
To investigate the benefits of scalable codecs in the case of rate adaptation problem, a streaming system for scalable H.264 videos has been implemented. The system considers congestion level in the network and buffer...
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To investigate the benefits of scalable codecs in the case of rate adaptation problem, a streaming system for scalable H.264 videos has been implemented. The system considers congestion level in the network and buffer status at the client during adaptation process. The rate adaptation algorithm is content adaptive. It selects an appropriate substream from the video file by taking into account the motion dynamics of video. The performance of the system has been tested under congestion-free and congestion scenarios. The performance results indicate that the system reacts to congestion properly and can be used for Internet video streaming where losses occur unpredictably.
scalable video coding and the quality of serves (QoS) is the next generation networks (NGN) key technique in order to adapt various clients' requirement (e.g. quality, spatial resolution and temporal resolution) a...
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ISBN:
(纸本)0889865442
scalable video coding and the quality of serves (QoS) is the next generation networks (NGN) key technique in order to adapt various clients' requirement (e.g. quality, spatial resolution and temporal resolution) and bandwidth variation in heterogeneous network. We propose a reduced dimension scalable video coding using wavelet transformation and QoS control method based on fractal interpolation for the next generation network, and realize different types of bit-stream decoders with different complexity and access bandwidth can coexist. Simulation result shows that the wavelet fractal interpolation algorithm bas better performance than the Bi-linear interpolation and no interpolation. When the channel is congests, the network is the lost high frequency sub-band and transmit low frequency sub-band, and the receiver can recover the lost high frequency by WFI or BLI to satisfy different clients' requirements.
This paper investigates the use of sparse overcomplete decompositions for audio coding. Audio signals are decomposed over a redundant union of modified discrete cosine transform (MDCT) bases having eight different sca...
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This paper investigates the use of sparse overcomplete decompositions for audio coding. Audio signals are decomposed over a redundant union of modified discrete cosine transform (MDCT) bases having eight different scales. This approach produces a sparser decomposition than the traditional MDCT-based orthogonal transform and allows better coding efficiency at low bitrates. Contrary to state-of-the-art low bitrate coders, which are based on pure parametric or hybrid representations, our approach is able to provide transparency. Moreover, we use a bitplane encoding approach, which provides a fine-grain scalable coder that can seamlessly operate from very low bitrates up to transparency. Objective evaluation, as well as listening tests, show that the performance of our coder is significantly better than a state-of-the-art transform coder at very low bitrates and has similar performance at high bitrates. We provide a link to test soundfiles and source code to allow better evaluation and reproducibility of the results.
In this paper, we propose efficient peer assignment algorithms for low-latency transmission of scalable coded images in peer-to-peer networks, in which peers may dynamically join and leave the networks. The objective ...
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In this paper, we propose efficient peer assignment algorithms for low-latency transmission of scalable coded images in peer-to-peer networks, in which peers may dynamically join and leave the networks. The objective of our algorithm is to minimize the transmission time of a requested image that is scalable coded. When an image is scalable coded in different bit rates, the bit stream encoded in a lower bit rate is a prefix subset of the one encoded in a higher bit rate. Therefore, a peer with the same requested image coded in any bit rate, even when it is different from the requested rate, may work as a supplying peer. As a result, when a scalable coded image is requested, more supplying peers can be found in peer-to-peer networks to help with the transfer. However, the set of supplying peers is not static during transmission, as the peers in this set may leave the network or finish their transmission at different times. The proposed peer assignment algorithms have taken into account the above constraints. In this paper, we first prove the existence of an optimal peer assignment solution for a simple identity permutation function, and then formulate peer assignment with this identity permutation as a mixed-integer programming problem. Next, we discuss how to address the problem of dynamic peer departures during image transmission. Finally, we carry out experiments to evaluate the performance of proposed peer assignment algorithms.
ITU-T has selected the candidate submitted by Ericsson, Nokia, Motorola, VoiceAge, and Texas Instruments as the baseline for the ***-VBR coding standard. ***-VBR is an embedded scalable speech codec that uses state-of...
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ISBN:
(纸本)9781424414833
ITU-T has selected the candidate submitted by Ericsson, Nokia, Motorola, VoiceAge, and Texas Instruments as the baseline for the ***-VBR coding standard. ***-VBR is an embedded scalable speech codec that uses state-of-the-art technology to provide the most efficient encoded speech available for various real-time applications. EV-VBR encodes both narrowband (NB) and wideband (WB) speech signals starting at 8kbps. Near perfect wideband representation is achieved at 32kbps for all signal types. The bit stream is divided into five robust layers, providing sufficient granularity, in particular for VoIP applications. In addition, an extension to the codec will provide super-wideband and stereo capability by adding layers to the codec. Extensive listening tests were conducted during the ITU-T selection phase to support selection of the best-performing candidate. The selected EV-VBR candidate passed 69 of 70 required and 25 of 28 objective terms of reference [1].
This paper presents a novel multi-filtering framework for achieving scalable PAttern-driven Region-adaptive Compression (SPARC) of imagery. Based on a pattern-driven image perception, SPARC achieves efficient compress...
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ISBN:
(纸本)9781424421787
This paper presents a novel multi-filtering framework for achieving scalable PAttern-driven Region-adaptive Compression (SPARC) of imagery. Based on a pattern-driven image perception, SPARC achieves efficient compression by modeling and encoding different (simple, structural and complex) visual patterns. Experimental results using various image datasets and comparison with the latest image compression standard corroborate the feasibility and efficiency of the SPARC technique.
We present the ***-VBR winning candidate codec recently selected by Question 9 of Study Group 16 (Q9/16) of ITU-T as a baseline for the development of a scalable solution for wideband speech and audio compression at r...
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ISBN:
(纸本)9781424414833
We present the ***-VBR winning candidate codec recently selected by Question 9 of Study Group 16 (Q9/16) of ITU-T as a baseline for the development of a scalable solution for wideband speech and audio compression at rates between 8 kb/s and 32 kb/s. The Q9/16 codec is an embedded codec comprising 5 layers where higher layer bitstreams can be discarded without affecting the decoding of the lower layers. The two lower layers are based on the CELP technology where the core layer takes advantage of signal classification based encoding. The higher layers encode the weighted error signal from lower layers using overlap-add transform coding. The codec has been designed with the primary objective of a high-performance wideband speech coding for error-prone telecommunications channels, without compromising the quality for narrowband/wideband speech or wideband music signals. The codec performance is demonstrated with selected test results.
It is envisioned that access networks will be mostly wireless in the future. Hence, it is of interest to consider extensions of the Datagram Congestion Control Protocol (DCCP) for wireless networks. This paper focuses...
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ISBN:
(纸本)9781424417650
It is envisioned that access networks will be mostly wireless in the future. Hence, it is of interest to consider extensions of the Datagram Congestion Control Protocol (DCCP) for wireless networks. This paper focuses on the problems of video streaming over DCCP in the wireless domain and proposes a cross-layer solution in which the wireless packet loss information available in the Medium Access (MAC) layer is utilized by DCCP to distinguish congestion losses from wireless losses and behave accordingly. Tests performed with our modified DCCP confirm that using cross-layer loss information prevents unnecessary rate decreases and results in better video streaming experiences.
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