Wireless Video Communication Research Articles

Denoising and Resource Allocation in Uncoded Video Transmission

The recently revitalized uncoded transmission has shown great potential in handling channel variations and user heterogeneities for wireless video communications. In this paper, we propose to adopt motion-compensated temporal filtering (MCTF) at the sender and denoising techniques at the receiver to fully exploit the temporal and spatial redundancy in video signals and therefore significantly improve the efficiency of uncoded video transmission. Although there are readily applicable MCTF and denoising techniques, integrating them into the uncoded video transmission framework is nontrivial, especially in the case of denoising. To address these challenges, we first propose spatial-domain transmission and cascaded denoising to harness the potential of denoising techniques. Second, we develop novel resource allocation algorithms based on variable-size L-shaped chunk division, which are not only compatible with spatial-domain transmission, but also achieves better energy efficiency than existing schemes based on fixed-size rectangular chunks. Our experimental results show that when transmitting 720p videos, our scheme achieves up to a 3.3 dB gain in video PSNR over the state-of-the-art uncoded transmission scheme SoftCast and up to a 5.3 dB gain over a digital scheme based on robust rate adaptation and H.264 scalable video coding (SVC).

Optimal Foresighted Multi-User Wireless Video

Recent years have seen an explosion in wireless video communication systems. Optimization in such systems is crucial – but most existing methods intended to optimize the performance of multi-user wireless video transmission are inefficient. Some works (e.g., Network Utility Maximization (NUM)) are myopic: they choose actions to maximize instantaneous video quality while ignoring the future impact of these actions. Such myopic solutions are known to be inferior to foresighted solutions that optimize the long-term video quality. Alternatively, foresighted solutions such as rate-distortion optimized packet scheduling focus on single-user wireless video transmission, while ignoring the resource allocation among the users. In this paper, we propose a general framework of foresighted resource allocation among multiple video users sharing a wireless network. Our framework allows each user to flexibly choose individual cross-layer strategies. Our proposed resource allocation is optimal in terms of the total payoff (e.g., video quality) of the users. A key challenge in developing foresighted solutions for multiple video users is that the users' decisions are coupled. To decouple the users' decisions, we adopt a novel dual decomposition approach, which differs from the conventional optimization solutions such as NUM, and determines foresighted policies. Specifically, we propose an informationally-decentralized algorithm in which the network manager updates state- and user-dependent resource “prices” (i.e., the dual variables associated with the resource constraints), and the users make individual packet scheduling decisions based on these prices. Because a priori knowledge of the system dynamics is almost never available at run-time, the proposed solution can learn online while performing the foresighted optimization. Simulation results show 7 dB and 3 dB improvements in Peak Signal-to-Noise Ratio (PSNR) over myopic solutions and existing foresighted solutions, respectively.

Video Transmission Over Lossy Wireless Networks: A Cross-Layer Perspective

Video content currently makes up nearly half of the “fixed” Internet traffic and more than a third of the mobile traffic in North America, with most other regions showing similar trends. As mobile data rates continue to increase and more people rely on 802.11 wireless for home and commercial Internet access, the amount of video transmitted over at least one wireless hop will likely continue to increase. In addition, as cameras continue to become smaller and cheaper, the demand for video services in sensor and MANET networks will also increase. In this paper, we examine the state of the art of wireless video communication at each layer of the networking stack. We consider both existing and emerging technologies at each layer of the protocol stack as well as cross-layer designs, and discuss how these solutions can increase the video experience for the end user.

An Advanced Moving Object Detection Algorithm for Automatic Traffic Monitoring In Real-World Limited Bandwidth Networks

Machine-controlled motion detection technology is Associate in nursing integral element of intelligent transportation systems, and is especially essential for management of traffic and maintenance of traffic police investigation systems. Traffic police investigation systems mistreatment video communication over real-world networks with restricted information measure typically encounter difficulties attributable to network congestion and/or unstable information measure. This is often particularly problematic in wireless video communication. This has necessitated the event of a rate management theme that alters the bit-rate to match the procurable network information measure, thereby manufacturing variable bit-rate video streams. However, complete and correct detection of moving objects beneath variable bit-rate video streams could be a terribly tough task. During this paper, we tend to propose Associate in nursing approach for motion detection that utilizes Associate in nursing analysis - primarily based radial basis perform network as its principal element. This approach is applicable not solely in high bit-rate video streams, however in low bit- rate video streams, as well. The planned approach consists of a varied background generation stage and a moving object detection stage. Throughout the assorted background generation stage, the lower-dimensional Eigen-patterns and also the adjustive background model are established in variable bit -rate video streams by mistreatment the planned approach so as to accommodate the properties of variable bit-rate video streams. Throughout the moving object detection stage, moving objects are extracted via the planned approach in each low bit -rate and high bit- rate video streams; detection results are then generated through the output worth of the planned approach. The detection results created through our approach indicate it to be extremely effective in variable bit-rate video streams over real-world restricted information measure networks. Additionally, the planned methodology will be simply achieved for period of time application. Quantitative and qualitative evaluations demonstrate that it offers blessings over different state- of-the -art ways. For example, and accuracy rates created via the planned approach were up to eighty six.38% and 89.88% beyond those created via different compared ways.

Delay—Power-Rate-Distortion Model for Wireless Video Communication Under Delay and Energy Constraints

Smart mobile phones are capable of performing video coding and streaming over wireless networks, but are often constrained by the end-to-end delay requirement and energy supply. To achieve optimal performance under the delay and energy constraints, in this paper we extend the traditional rate-distortion (R-D) model and the previously proposed delay R-D model to a novel delay-power-rate-distortion (d-P-R-D) model by including another two dimensions (the encoding time and encoder power consumption), which quantifies the relationship among source encoding delay, rate, distortion, and power consumption for IPPPP coding mode in H.264/AVC. We have verified the accuracy of our proposed d-P-R-D model through experiments. Based on the proposed d-P-R-D model, we develop a novel rate-control (RC) algorithm, which minimizes the encoding distortion under the constraints of rate, delay, and power. The experimental results demonstrate the superiority of the proposed RC algorithm over the existing scheme. Therefore, the d-P-R-D model and the model-based RC provide a theoretical basis and a practical guideline for the cross-layer system design and performance optimization in wireless video communication under delay and energy constraints.

An Advanced Moving Object Detection Algorithm for Automatic Traffic Monitoring in Real-World Limited Bandwidth Networks

Automated motion detection technology is an integral component of intelligent transportation systems, and is particularly essential for management of traffic and maintenance of traffic surveillance systems. Traffic surveillance systems using video communication over real-world networks with limited bandwidth often encounter difficulties due to network congestion and/or unstable bandwidth. This is especially problematic in wireless video communication. This has necessitated the development of a rate control scheme which alters the bit-rate to match the obtainable network bandwidth, thereby producing variable bit-rate video streams. However, complete and accurate detection of moving objects under variable bit-rate video streams is a very difficult task. In this paper, we propose an approach for motion detection which utilizes an analysis-based radial basis function network as its principal component. This approach is applicable not only in high bit-rate video streams, but in low bit-rate video streams, as well. The proposed approach consists of a various background generation stage and a moving object detection stage. During the various background generation stage, the lower-dimensional Eigen-patterns and the adaptive background model are established in variable bit-rate video streams by using the proposed approach in order to accommodate the properties of variable bit-rate video streams. During the moving object detection stage, moving objects are extracted via the proposed approach in both low bit-rate and high bit-rate video streams; detection results are then generated through the output value of the proposed approach. The detection results produced through our approach indicate it to be highly effective in variable bit-rate video streams over real-world limited bandwidth networks. In addition, the proposed method can be easily achieved for real-time application. Quantitative and qualitative evaluations demonstrate that it offers advantages over other state-of-the-art methods. For instance, Similarity and F1 accuracy rates produced via the proposed approach were up to 86.38% and 89.88% higher than those produced via other compared methods, respectively.

Highly accurate moving object detection in variable bit rate video-based traffic monitoring systems.

Automated motion detection, which segments moving objects from video streams, is the key technology of intelligent transportation systems for traffic management. Traffic surveillance systems use video communication over real-world networks with limited bandwidth, which frequently suffers because of either network congestion or unstable bandwidth. Evidence supporting these problems abounds in publications about wireless video communication. Thus, to effectively perform the arduous task of motion detection over a network with unstable bandwidth, a process by which bit-rate is allocated to match the available network bandwidth is necessitated. This process is accomplished by the rate control scheme. This paper presents a new motion detection approach that is based on the cerebellar-model-articulation-controller (CMAC) through artificial neural networks to completely and accurately detect moving objects in both high and low bit-rate video streams. The proposed approach is consisted of a probabilistic background generation (PBG) module and a moving object detection (MOD) module. To ensure that the properties of variable bit-rate video streams are accommodated, the proposed PBG module effectively produces a probabilistic background model through an unsupervised learning process over variable bit-rate video streams. Next, the MOD module, which is based on the CMAC network, completely and accurately detects moving objects in both low and high bit-rate video streams by implementing two procedures: 1) a block selection procedure and 2) an object detection procedure. The detection results show that our proposed approach is capable of performing with higher efficacy when compared with the results produced by other state-of-the-art approaches in variable bit-rate video streams over real-world limited bandwidth networks. Both qualitative and quantitative evaluations support this claim; for instance, the proposed approach achieves Similarity and F1 accuracy rates that are 76.40% and 84.37% higher than those of existing approaches, respectively.

Editorial: recent advances in communication networks and multimedia technologies

To successfully support multimedia applications, it is necessary to improve the state-of-theart multimedia technologies and multimedia transmissions over communication networks in order to provide quality-of-service (QoS) guarantees between end-users and to achieve a high quality-of-experience for end-users. The accepted papers in this special issue deal with a wide range of important aspects and challenging issues of communication networks and multimedia technologies, and the contents are built on analytical modelling, experimental and simulation studies. The contributions of these papers are outlined below. With the development of wireless access and multimedia compression technologies, much attention has been devoted to wireless video communications. Wan, Xiong and Yang propose an integrated routing metric to evaluate path quality taking the hop count, congestion bottleneck and other parameters of a path into account. They design the traffic assignment and traffic adjustment modules to make the routing scheme flexible to the changing environments, and present an enhanced link layer scheduling algorithm. Simulation results show that compared to commonly used schemes, the proposed network layer scheme always provides better performance with various traffic modes; combined with link layer scheduling algorithm, the performance could be further improved. High speed and quality multimedia and data transmission requirements exist widely in wireless networks. Wang et al. investigate the performance of opportunistic scheduling in wireless multimedia and data networks based on popular stochastic network calculus (SNC). The authors firstly bound the traffic arrival process using the exponentially bounded burstiness traffic model of SNC and establish a stochastic arrival curve, and then propose a new wireless opportunistic scheduling, i.e., modified proportional fairness (MPF) scheduling algorithm, which can provide better fairness for input traffic to guarantee QoS performance, and obtain a stochastic service curve. The numerical results show that the proposed stochastic model and MPF scheduling algorithm can provide better QoS performance. Multimed Tools Appl (2015) 74:1–3 DOI 10.1007/s11042-013-1647-x

Impact of Transmission Distortion on Video Streaming Quality over China Mobile Multimedia Broadcast

This paper investigates the perceptual quality of video streams affected by wireless channel transmission distortion over CMMB (China Mobile Multimedia Broadcasting standards). First, transmission distortion is simulated using block error rate patterns representative of the wireless channel. Finally, we provide an asymptotic quality analysis of the video transmission through CMMB wireless channel. It can evaluate video streams quality of CMMB and get a good corresponding with the subjective assessments results. This type of quality assessment model based on transmission distortion has important applications in real-time wireless video communication.

Smart Broadcast Technique for Improved Video Applications over Constrained Networks

improved wireless video communication is challenging since video stream is vulnerable to channel distortions. Hence, the need to investigate efficient scheme for improved video communications. This research work investigated broadcast schemes, and proposes smart broadcast technique as a solution for improved video quality over constrained network such as wireless network under tight constraints. The scheme exploits the concept of video analysis and adaptation principles in the optimization process. The experimental results obtained under different channel conditions demonstrate the capability of the proposed scheme in terms of improving the average received video quality performance over a constrained network.

Binomial Bit-Rate Computation Model Based on Wireless Channel

For the encoding bit-rate problem in H.264 wireless video communication, the bit-rate computation model and the standard deviation distortion model were analyzed to establish the relation between the quantization parameter of encoding bit-rate and the intra-frame refresh rate of macroblocks, a new proposal of the coding rate thus put forward based on the general binomial computation model theory. Furthermore, this method not only can adaptively adjust the bit allocation and quantization parameters to prevent buffer from overflowing downward or upward under given network bandwidth, but also can apply the rate-distortion to perfect the solution method, control the encoding bits accurately and optimize the allocation between the inter-frame encoding macroblocks.

Evaluation on Multiple Video Streaming in IEEE 802.11e Multihop Networks

In the last decade, both customers and researchers paid attention to wireless video communications applications because they contain abundant and visual information. However, characteristics of wireless networks such as limited resource and fluctuated link quality degrade video transmission quality. In this paper, multiple video streaming in IEEE 802.11e multihop networks is evaluated under different conditions to find out how to design an adaptive cross-layer video transmission scheme for multi-stream transmission. On one hand, we compare the performances of multipath routing and single path routing. On the other hand, EDCA and its two modifications are evaluated to verify their flexibility. Evaluation results show that the performance of multi-stream video transmission depends on many factors, including data rates and coding structures of video sequences, traffic assignment mechanism, data rates of background data streams, etc.

Wyner-Ziv video coding for wireless lightweight multimedia applications

Wireless video communications promote promising opportunities involving commercial applications on a grand scale as well as highly specialized niche markets. In this regard, the design of efficient video coding systems, meeting such key requirements as low power, mobility and low complexity, is a challenging problem. The solution can be found in fundamental information theoretic results, which gave rise to the distributed video coding (DVC) paradigm, under which lightweight video encoding schemes can be engineered. This article presents a new hash-based DVC architecture incorporating a novel motion-compensated multi-hypothesis prediction technique. The presented method is able to adapt to the regional variations in temporal correlation in a frame. The proposed codec enables scalable Wyner-Ziv video coding and provides state-of-the-art distributed video compression performance. The key novelty of this article is the expansion of the application domain of DVC from conventional video material to medical imaging. Wireless capsule endoscopy in particular, which is essentially wireless video recording in a pill, is proven to be an important application field. The low complexity encoding characteristics, the ability of the novel motion-compensated multi-hypothesis prediction technique to adapt to regional degrees of temporal correlation (which is of crucial importance in the context of endoscopic video content), and the high compression performance make the proposed distributed video codec a strong candidate for future lightweight (medical) imaging applications.

Rate-Distortion Optimized Cross-Layer Rate Control in Wireless Video Communication

A wireless video communication system can be designed based on the rate-distortion (R-D) criterion, i.e., minimizing the end-to-end distortion (which includes quantization distortion and transmission distortion) subject to the transmission bit-rate constraint. The minimization can be achieved by adjusting the source encoding parameters and channel encoding parameters. This rate-distortion optimization (RDO) is usually done for each video frame individually in a real-time video communication system, e.g., video calls or videoconferencing. To achieve this, an accurate bit-rate model and distortion model for each frame can be used to reduce the RDO complexity. In this paper, we derive a source bit-rate model and quantization distortion model; we also improve the performance bound for channel coding under a convolutional code and a Viterbi decoder, and derive its performance bound under a Rayleigh block fading channel. Given the instantaneous channel condition, e.g., signal-to-noise ratio and transmission bit-rate constraint, we design an R-D optimized cross-layer rate control (CLRC) algorithm by jointly choosing quantization step size in source coding and code rate in channel coding. Experimental results show that our proposed R-D models are more accurate than the existing R-D models. Experimental results also showed that the rate control under our models has more stable R-D performance than the existing rate control algorithms; using the channel estimation, CLRC can further achieve remarkable R-D performance gain over that without channel estimation. Another important result is that the subjective quality of our CLRC algorithm is much better than the existing algorithms due to its intelligent reference frame selection.

IMPROVING QUALITY OF SERVICE USING OFDM TECHNIQUE FOR 4TH GENERATION NETWORK

The migration to 4G networks will bring a new level of expectation to wireless communications. As after digital wireless revolution made mobile phones available for everyone, the higher speeds and packet delivery of 4G networks will make high quality multimedia available everywhere. The key to achieving this higher level of service delivery is a new air interface, OFDM, which is in turn enabled by the high level of performance. OFDM provides a robust signal that requires relatively little power yet uses bandwidth very efficiently. Carriers will benefit from greater flexibility by using OFDM, since in the same spectrum they will be able to offer more channels, including higher ‘bandwidth channels, with more types of services. Currently these systems are still being defined and prototyped. Achieving higher data rates requires OFDM systems to make more efficient use of the bandwidth than CDMA systems. One method of achieving this higher efficiency is through the use of higher order modulation. In this paper we have compared two digital modulation techniques 32QAM and 64QAM used for digital transmission of data. Our main objective to develop this configuration is to compare the performance of each modulation techn iques. Comparison is done by Bit Error Rate analysis of both modulation techniques. We have developed existing configurations and improved them with high quality senders and receivers using MATLAB technology. In this paper we have also considered how OFDM can improve the real time video streaming over the wireless network. We have considered the problem of multiuser video streaming over OFDM. OFDM is a multi carrier modulation. The growing interest in Multicarrier Transmission by researchers and product developers motivated us to propose this topic for a special issue of Wireless Video transmission and Communications.

It's Time to Unify Telecommunications Policy

Abstract Rooted in 20th century legislation, telecommunications policy has historically been conducted in separate wired and wireless silos. The explosion of wireless voice, data and video communications, however, has largely overtaken wired communications, yet these silos persist. This article evaluates the economic foundation for unifying telecommunications policy.

Prediction of Transmission Distortion for Wireless Video Communication: Analysis

Transmitting video over wireless is a challenging problem since video may be seriously distorted due to packet errors caused by wireless channels. The capability of predicting transmission distortion (i.e., video distortion caused by packet errors) can assist in designing video encoding and transmission schemes that achieve maximum video quality or minimum end-to-end video distortion. This paper is aimed at deriving formulas for predicting transmission distortion. The contribution of this paper is twofold. First, we identify the governing law that describes how the transmission distortion process evolves over time and analytically derive the transmission distortion formula as a closed-form function of video frame statistics, channel error statistics, and system parameters. Second, we identify, for the first time, two important properties of transmission distortion. The first property is that the clipping noise, which is produced by nonlinear clipping, causes decay of propagated error. The second property is that the correlation between motion-vector concealment error and propagated error is negative and has dominant impact on transmission distortion, compared with other correlations. Due to these two properties and elegant error/distortion decomposition, our formula provides not only more accurate prediction but also lower complexity than the existing methods.

Prediction of transmission distortion for wireless video communication: Algorithm and application

In this paper, we develop algorithms for estimating transmission distortion in wireless video communication systems. By leveraging the analytical results obtained in our previous works, we design low complexity algorithms that are capable of estimating transmission distortion accurately. We also extend our algorithm for pixel-level transmission distortion estimation to pixel-level end-to-end distortion estimation. Furthermore, we apply our pixel-level end-to-end distortion estimation algorithm to prediction mode decision in H.264 encoder. Experimental results show that (1) our transmission distortion estimation algorithm is more accurate and more robust against inaccurate channel estimation than existing distortion estimation algorithms; (2) our mode decision algorithm achieves remarkable PSNR gain over the existing algorithms for prediction mode decision in H.264 encoder, e.g., an average PSNR gain of 1.44 dB for ‘foreman’ sequence when Packet Error Probability (PEP) equals 5%.

Cross-layer wireless video adaptation: Tradeoff between distortion and delay

Adaptive scheduling is becoming an increasingly important issue in wireless video communications, which are widely used in the industry and academic organizations. However, existing scheduling schemes for real-time video services in wireless networks generally do not take into account the relationship between the transmission delay and video distortion. In this paper, we develop and evaluate a delay-distortion-aware wireless video scheduling scheme in the framework of cross-layer information adaptation. At first, we construct a general video distortion model according to the observed wireless network parameters, as well as each video sequence’s rate-distortion characteristic. Then, we exploit a distortion-aware wireless video scheduling scheme and derive a bound on the asymptotic decay rate of the video distortion. Furthermore, the relationship between the delay and distortion is studied by taking into account video application delay and distortion requirements for specific wireless network environments. The proposed scheme is applied to heuristically find optimal tradeoff between the delay and distortion. Extensive examples are provided to demonstrate the effectiveness and feasibility of the proposed scheme.

Rate control in H.264 wireless video communication system

PurposeThe purpose of this paper is to introduce an efficient rate control algorithm for the H.264/AVC video coding in wireless communication. The adaptive rate control algorithm can reduce rate fluctuation, effectively prevent the skipping frame, and be suitable to the characteristics of wireless channel. The experimental result indicates that this plan can guarantee the quality of service of video transmission.Design/methodology/approachA motion complexity measure is developed to enhance the existing mean of absolute difference (MAD)‐based algorithm and is applied to bit allocation for rate control. Time and space relativities in frames are also used in the proposed rate control algorithm for MAD prediction. A quantitative parameter (QP) control scheme is used to adjust the computed QP based on actual encoding results of previous coded macroblocks (MBs) in a frame.FindingsThe proposed rate control algorithm always outperforms JM 8.6. The adaptive MAD model can reduce the prediction error. Both the subjective and objective reconstructed video qualities are improved, and the luminance PSNR is increased by up to 0.53 dB (or an average of around 0.37 dB).Originality/valueThe adaptive rate control algorithm based on motion complexity and MAD prediction with space and time relativities will be suitable for wireless communication applications.