The Versatile Video Coding (VVC) standard was released in 2020 to replace the High Efficiency Video Coding (HEVC) standard, making it necessary to convert HEVC encoded content to VCC to exploit its compression performance, which was achieved by using a larger block size of 128 × 128 pixels, among other new coding tools. However, 80.93% of the encoding time is spent on finding a suitable block partitioning. To reduce this time, this proposal presents an HEVC-to-VVC transcoding algorithm focused on accelerating the CTU partitioning decisions. The transcoder takes different information from the input bitstream of HEVC, and feeds it to two Bayes-based models. Experimental results show a time saving in the transcoding process of 45.40%, compared with the traditional cascade transcoder. This time gain has been obtained on average for all test sequences in the Random Access scenario, at the expense of only 1.50% BD-rate.

In the coming years, the Versatile Video Coding (VVC) standard will be launched to replace the current High Efficiency Video Coding (HEVC) standard, making it necessary to find efficient methods to convert existing multimedia content to the new format. However, transcoding is a complex pipeline composed of a decoding and an encoding process that involves long processing times. On the basis of the existing correlation between the block partitioning structures of both standards, this paper presents an HEVC-to-VVC transcoding scheme. The proposed method consists of a Naïve-Bayes classifier that assists the partitioning decision at the first level of quadtree by using features extracted from the $128\times 128$ pixel blocks of the residual and reconstructed frames in HEVC. The experimental results using random access configuration show an average transcoding time reduction of 13.38% at the cost of a compression efficiency loss of 0.32% in terms of BD-rate.

High Efficiency Video Coding (HEVC) has become the state-of-the-art video coding standard. It outperforms its predecessors by the introduction of new coding tools, such as the new quadtree-based partitioning scheme called the coding tree unit (CTU), which enables a more flexible partitioning of the input frames. However, selecting the optimal partitioning requires the evaluation of numerous possibilities, which involves long computing times that hinder the applicability of the standard in real-world scenarios. With this in mind, the main focus of this paper is on tackling this complexity by means of a fast partitioning and mode decision algorithm based on a look-ahead stage. This stage performs a preliminary motion estimation that provides the motion costs used to build the least-cost quadtree, which is in turn utilized to conduct the encoding itself. On the basis of this quadtree, the encoder may decide to terminate the partitioning early, or to evaluate additional depth levels adaptively. Furthermore, the encoder may omit some prediction modes according to the costs estimated by the look-ahead stage. A thorough experimental evaluation of the algorithm shows that it can reduce the encoding time by 65.33%, at the expense of only a 1.35% BD-rate for the random access configuration. Combined with a fast inter prediction algorithm, this reduction can rise to 70.55%, while the coding efficiency is maintained at a 1.83% BD-rate. When compared with other related works, these results display an excellent trade-off between the two variables.

In the last few years new devices with different computational capabilities and network connections has emerged, and this leads to the need for more adaptable video streams. The last two video coding standards, namely H.264/Advanced Video Coding and High Efficiency Video Coding, have defined scalable versions of themselves that provide this adaptability by the use of several layers with different levels of quality, frame rates, and resolutions. Moreover, HEVC introduced hybrid scalability, which allows a non-HEVC base layer (e.g., H.264/AVC) in combination with HEVC enhancement layers, what provides backwards compatibility with older devices. Nevertheless, scalable video coding is very computationally expensive, making it necessary to accelerate the video encoding. This paper presents a fast Coding Unit size algorithm for the combination of hybrid and temporal scalabilities that is based on machine learning. Experimental results show that an acceleration of 54% is achieved at the cost of a slight increment in the bit rate.

The High Efficiency Video Coding (HEVC) standard has shown large improvements in coding efficiency compared with previous standards. In particular, HEVC outperforms H.264/MPEG-4 Advanced Video Coding by up to 50% in terms of bitrate reduction for similar perceptual quality. This improvement is the result of the introduction of new coding tools, which enable the representation of data using fewer bits, but at the cost of long computation times. One of the most significant tools introduced by HEVC is the novel quadtree-based structure called the coding tree unit (CTU), which can be subsequently split into coding units (CUs), prediction units (PUs), and transform units (TUs), providing huge flexibility in the encoding. However, selecting the optimal tree partitioning requires the evaluation of a huge number of possibilities, which constitutes the most complex operation for the encoder. In order to tackle this task, this paper proposes a CTU/CU partitioning algorithm based on a pre-analysis stage. This stage performs a fast motion estimation that provides preliminary information to the encoder, including estimate distortion costs, which enables the building of the least-cost quadtree. On the basis of this tree, the evaluation performed by the encoder is restricted to a subset of PUs. After a thorough statistical analysis of numerous CU/PU combinations, we propose two different configurations that prioritize each of the target variables: coding efficiency and time reduction. In the former case, 58.09% of the encoding time can be saved at the cost of a 2.51% increase in Bjøntegaard delta (BD)-rate, while a larger reduction of 63.08% is achieved with a 3.43% increase in BD-rate in the later case.

The High Efficiency Video Coding (HEVC) standard roughly doubles the rate-distortion compression performance of its predecessor, H.264/AVC, at a cost of a high computational complexity. Moreover, intra sequences are commonly used at video editing or post-production, making it necessary a migration from H.264/AVC to HEVC. This paper aims to propose a fast intra transcoding algorithm from H.264/AVC to HEVC.

The demands for high quality multimedia contents and the advent of the Ultra High Definition (UHD) resolution have motivated the development of the High Efficiency Video Coding (HEVC) standard, which outperforms prior standards by up to 50% in terms of coding efficiency. This improvement, however, involves higher computational complexity in the encoder side, making it essential for realtime encoders to implement fast and efficient coding algorithms. In this regard, this paper proposes a pre-analysis algorithm designed to provide coding information to the motion estimation (ME) stage of the encoder. This algorithm, which takes into consideration the particularities of this new standard, makes use of this information to reduce the number of tested reference frames and the number of positions checked in the motion search. As a result, an experimental evaluation of the algorithm shows that it allows reducing the encoding time by 16.10% average with negligible losses in terms of coding efficiency.

High Efficiency Video Coding (HEVC) was developed by the Joint Collaborative Team on Video Coding to replace the current H.264/Advanced Video Coding (AVC) standard, which has dominated digital video services in all segments of the domestic and professional markets for over ten years. Therefore, there is a lot of legacy content encoded with H.264/AVC, and an efficient video transcoding from H.264/AVC to HEVC will be needed to enable gradual migration to HEVC. In terms of rate-distortion (RD) performance, HEVC roughly doubles the RD compression performance of H.264/AVC at the expense of a high computational cost. HEVC adopts a quadtree-based coding unit (CU) block partitioning structure that is flexible in adapting various texture characteristics of images. However, this causes a dramatic increase in computational complexity due to the necessity of finding the best CU partitions. This paper presents an adaptive fast quadtree level decision algorithm that is designed to exploit the information gathered at the H.264/AVC decoder in order to make faster decisions on CU splitting in HEVC using a Naïve-Bayes probabilistic classifier that is determined by a supervised data mining process. The experimental results show that the proposed algorithm can achieve a good tradeoff between coding efficiency and complexity compared with the anchor transcoder; moreover, it outperforms other related works available in the literature.

High Efficiency Video Coding was developed by the JCT-VC to replace the current H.264/AVC standard, which has dominated digital video services in all segments of the domestic and professional markets for over ten years. Therefore, there is a lot of legacy content encoded with H.264/AVC, and an efficient video transcoding from H.264 to HEVC will be needed to enable gradual migration to HEVC. HEVC adopts a quad tree-based Coding Unit block partitioning structure that is flexible in adapting various texture characteristics at the expense of a high computational cost. This paper presents a data-driven probabilistic CTU splitting algorithm that is designed to exploit the information gathered at the H.264/AVC decoder in order to make faster decisions on CU splitting in HEVC. Experimental results show that the proposed algorithm can achieve a good tradeoff between coding efficiency and complexity compared with the anchor transcoder, and, moreover, it outperforms other related works available in the literature.

The rapid emergence and rise of a wide range of electronic devices has led to the need for providing very different levels of video transmission services. The capabilities and performance of these devices determine the type of video streams that they are able to decode. As a way to fulfil their requirements, this paper presents a heterogeneous simultaneous encoding framework of H.264/Advanced Video Coding (AVC) and High Efficiency Video Coding (HEVC) that shares information between encoders in order to reduce the overall encoding time. In this regard, the proposed approach utilizes the H.264/AVC motion vectors of the 16x16 pixels macroblocks as predictors for the HEVC prediction units. As a consequence, the size of the motion estimation search area can be significantly reduced. Results show that an encoding time reduction of 8.95% can be achieved with negligible losses in terms of rate-distortion.

We propose a technique for optimizing the High Efficiency Video Coding (HEVC) encoder by reducing the number of operations performed in the motion estimation stage. The technique is based on the fact that a significant number of motion estimation operations are performed repetitively for the same image samples, but for different block partition sizes. By decoupling the initial motion estimation and the block partitioning into different stages it is possible to remove a considerable number of redundant motion estimation operations. An implementation of the proposed technique on a SIMD optimized version of the HEVC reference encoder shows that, on average, a reduction of 79.02% SAD operations can be achieved, that results in an average reduction of 14.63% of the encoding complexity with negligible impact on the compression efficiency (BD-rate losses of less than 1%).

The High Efficiency Video Coding (HEVC) was developed by the Joint Collaborative Team on Video Coding (JCT-VC) to replace the current H.264/AVC standard which has been widely adopted in the last years. Therefore, there is a lot of legacy content encoded with H.264/AVC and an efficient conversion to HEVC is needed. This paper, presents a Fast Quadtree Level Decision (FQLD) algorithm that greatly reduces the complexity of the transcoding process between H.264/AVC and HEVC. The proposal tries to exploit the information gathered at the H.264/AVC decoder to make decisions on Coding Units (CU) splitting in HEVC using a Naïve-Bayes (NB) probabilistic classifier. Experimental results show that the proposed transcoder can achieve a good tradeoff between coding efficiency and complexity.

High Efficiency Video Coding (HEVC) is the new video coding standard recently approved by ISO and ITU. HEVC allows a bit rate reduction greater than a 50% with respect to its predecessor, the H.264/AVC, offering the same perceptual quality, by means of a set of new tools that have been introduced. Compared with the current state of the art in image coding, such as JPEG, JPEG2000 or the new JPEG XR, the new Intra Frame coding performs a high compression process in the "All-Intra" mode. All these improvements are at expense of a high computational cost, making it considerably difficult to implement in real time. Hence, this paper presents a mechanism that can be used by the RDO algorithm to select the optimal coding block size for Intra-Prediction, by using a data mining classifier, based on a previous training. Experimental results show that the proposed algorithm can achieve a 30% of Time Savings over a wide range of high resolution sequences (Class A, B and F), with a negligible loss of coding efficiency.

Nowadays, networks and terminals with diverse characteristics of bandwidth and capabilities coexist. To ensure a good quality of experience, this diverse environment demands adaptability of the video stream. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a technique to convert an H.264/AVC bitstream without scalability to a scalable bitstream with temporal scalability in Main Profile by accelerating the mode decision task of the SVC encoding stage using Machine Learning tools. The results show that when our technique is applied, the complexity is reduced by 87% while maintaining coding efficiency.

Scalable video coding (SVC) allows encoded bitstreams to be adapted. However, most bitstreams do not incorporate this scalability so bitstreams have to be adapted multiple times to accommodate for varying network conditions or end-user devices. Each adaptation incorporates an additional loss of quality due to transcoding. To overcome this issue, we propose a single transcoding step from H.264/AVC to SVC. Doing so, the resulting bitstream can be freely adapted without any additional quality reduction. Open-loop transcoding architectures can be used for H.264/AVC-to-SVC transcoding with a low complexity, although these architectures suffer from drift artifacts. Closed-loop transcoding, on the other hand, requires a higher complexity. To overcome the drawbacks of both systems, we propose combining both techniques.

Scalable Video Coding (SVC) is a recent extension of the ISO/ITU Advanced Video Coding (H.264/AVC) standard, which allows adapting the bitstream easily by dropping some parts of it named as layers. This adaptation makes possible that the same bitstream meets the requirements for reliable delivery of video to diverse clients over heterogeneous networks using temporal, spatial or SNR scalability, combined or separately. Since the SVC design requires scalability to be provided at the encoder side, the existing contents cannot benefit of it. Efficient techniques for converting contents without scalability to a scalable format are desirable. In this paper, an approach for temporal scalability transcoding from H.264/AVC to SVC is presented and the impact of the GOP size is analyzed. Independently of the GOP size chosen, around a 60% of time saving is achieved while maintaining the coding efficiency. Moreover, this technique could be used to transform an H.264/AVC bitstream without temporal scalability to another H.264/AVC bitstream with hierarchical structures that provides temporal scalability.

Based on our previous efforts, we introduce in this letter a high-efficient MPEG-2 to H.264 transcoder for the baseline profile in the spatial domain. Machine learning tools are used to exploit the correlation between the macroblock (MB) decision of the H.264 video format and the distribution of the motion compensated residual in MPEG-2. Moreover, a dynamic motion estimation technique is also proposed to further speed-up the decision process. Finally, we go a step further on our previous research efforts by combining the two aforementioned speed-up approaches. Our simulation results over more than 40 sequences at common intermediate format and quarter common intermediate format resolutions show that our proposal outperforms the MB mode selection of the rate-distortion optimization option of the H.264 encoder process by reducing the computational requirements by up to 90%, while maintaining the same coding efficiency. Finally, we conduct a comparative study of our approach with the most relevant fast inter-prediction methods for MPEG-2 to H.264 transcoder recently reported in the literature.

This paper proposes an improved Wyner-Ziv to H.264 video transcoder as part of a framework for mobile to mobile video communications. In this scheme, the user devices keep the low complexity constraints by using the Wyner-Ziv encoding and H.264 decoding algorithms. They shift their complexities to the network where the proposed transcoder is allocated. The main goal of the transcoder is to convert the bitstream and reduce the delay efficiently. The results show that the proposed transcoder reduces the complexity by a factor of 95% with a negligible rate-distortion loss.

Distributed video coding (DVC), has been an interesting alternative to the conventional video coding for a number of applications because of its flexibility for designing extremely low complexity video encoders. The performance of DVC can be improved by only modifying the decoder to keep the encoder complexity at the same level. In this paper, we propose a novel modified framework for a DVC codec considering an iterative side information refinement technique. Refinement is performed at the decoder, first with the help of the decoded DC frame and then considering partially decoded frame using previously refined side information. By iteratively refining the side information, a significant improvement has been achieved in the rate distortion performance.

In mobile-to-mobile video communications, both the sender and the receiver devices should not have higher complexity requirements to perform complex video compression tasks. The traditional video coding solutions are not suitable to support this communications due to its extremely complex encoding algorithm. On the other hand, the new Wyner-Ziv video coding paradigm reduces the complexity of the encoder at the expenses of a more complex decoder. In this paper, we propose an improved WZ/H.264 video transcoder to support this mobile-to-mobile communications, using the low complexity Wyner-Ziv encoding and the traditional H.264 decoding to be implemented in the end-user devices. The improved transcoder converts the video from the Wyner-Ziv to H.264 and reuses the motion vectors generated in the Wyner-Ziv decoding, in order to reduce the computational complexity of the motion estimation process in the H.264 encoding. Simulations results show a complexity reduction up to 55% with negligible rate-distortion drop.

The authors develop a decoder/encoder system (transcoder) to solve the consumption constraint in the communications between end-user devices, when a new Wyner–Ziv (WZ)/H.264 framework is defined for being used in mobile-to-mobile environments. This approach is based on leaving to the devices only WZ video encoding and traditional video decoding; the lowest complexity algorithms in both paradigms. The system shifts the burden of complexity to the network, where an improved transcoder that reuses information between both paradigms is allocated. The WZ decoding motion vectors are used to reduce the H.264 motion estimation process. The proposed transcoder offers a complexity reduction up to 60% on average, without any rate distortion drop.

The H.264 standard achieves much higher coding efficiency than the MPEG-2 standard, due to its improved inter-and intra-prediction modes at the expense of higher computational complexity. Transcoding MPEG-2 video to H.264 is important to enable gradual migration to H.264. However, given the significant differences between the MPEG-2 and the H.264 coding algorithms, transcoding is a much more complex task and new approaches to transcoding are necessary. The main problems that need to be addressed in the design of an efficient heterogeneous MPEG-2/H.264 transcoder are: the inter-frame prediction, the transform coding and the intra-frame prediction. In this paper, we focus our attention on the inter-frame prediction, the most computationally intensive task involved in the transcoding process. This paper presents a novel macroblock (MB) mode decision algorithm for P-frame prediction based on machine learning techniques to be used as part of a very low complexity MPEG-2 to H.264 video transcoder. Since coding mode decisions take up the most resources in video transcoding, a fast MB mode estimation would lead to reduced complexity. The proposed approach is based on the hypothesis that MB coding mode decisions in H.264 video have a correlation with the distribution of the motion compensated residual in MPEG-2 video. We use machine learning tools to exploit the correlation and construct decision trees to classify the incoming MPEG-2 MBs into one of the several coding modes in H.264. The proposed approach reduces the H.264 MB mode computation process into a decision tree lookup with very low complexity. Experimental results show that the proposed approach reduces the MB mode selection complexity by as much as 95% while maintaining the coding efficiency. Finally, we conduct a comparative study with some of the most prominent fast inter-prediction methods for H.264 presented in the literature. Our results show that the proposed approach achieves the best results for video transcoding applications.

Recent developments have given birth to H.264/AVC: a video coding standard offering better bandwidth to video quality ratios than previous standards (such as H.263, MPEG-2, MPEG-4, etc.), due to its improved inter- and intraprediction modes at the expense of higher computation complexity. It is expected that H.264/AVC will take over the digital video market, replacing the use of previous standards in most digital video applications. This creates an important need for heterogeneous video transcoding technologies from older standards to H.264. In this paper, we focus our attention on the interframe prediction, the most computationally intensive task involved in the heterogeneous video transcoding process. This paper presents a novel macroblock (MB) mode decision algorithm for interframe prediction based on data mining techniques to be used as part of a very low complexity heterogeneous video transcoder. The proposed approach is based on the hypothesis that MB coding mode decisions in H.264 video have a correlation with the distribution of the motion compensated residual in the decoded video. We use data mining tools to exploit the correlation and derive decision trees to classify the incoming decoded MBs into one of the several coding modes in H.264. The proposed approach reduces the H.264 MB mode computation process into a decision tree lookup with very low complexity. For general validation purposes, we apply our algorithm to two of the most important heterogeneous video transcoders: MPEG-2 to H.264 and H.263 to H.264. Our results show that the our data-mining based transcoding algorithm is able to maintain a good video quality while considerably reducing the computational complexity by 72% on average when applied in MPEG-2 to H.264 transcoders, and by 62% on average when applied in H.263 to H.264 transcoders. Finally, we conduct a comparative study with some of the most prominent fast interprediction methods for H.264 presented in the literature. Our results show that the proposed data mining-based approach achieves the best results for video transcoding applications.

In this paper, we propose the use of data mining algorithms to create a macroblock partition mode decision algorithm for inter-frame prediction, to be used as part of a high-efficient H.263 to H.264 transcoder. We use machine learning tools to exploit the correlation and derive decision trees to classify the incoming H.263 MC residual into one of the several coding modes in H.264. The proposed approach reduces the H.264 MB mode computation process into a decision tree lookup with very low complexity. Experimental results show that the proposed approach reduces the inter-prediction complexity by as much as 60% while maintaining the coding efficiency.

The two key problems in video transcoding are complexity reduction and quality management. The complexity of H.264 encoding makes complexity reduction even more important. A good transcoder design reduces complexity with negligible loss in quality. While motion estimation complexity can be easily reduced by reducing the search range or eliminating the coding modes, these approaches will cause significant quality drop. This paper presents reduced complexity motion estimation for MPEG-2 to H.264 transcoding. The proposed approach uses MPEG-2 motion vectors to dynamically reduce the search range and the motion vector refinement window. This approach is based on the hypothesis that longer MPEG-2 motion vectors indicate higher motion and hence a larger search window as well as a larger refinement window is necessary. Experimental results show that the proposed approach reduces the motion estimation complexity by as much as 85% with negligible loss in PSNR. We show that the results hold across video resolutions and bitrates.

Distributed video coding (DVC) is an increasingly popular approach among the researchers in video coding during past few years due to its attractive and promising features. In DVC, the majority of the computational complexity has been shifted from encoder to the decoder in comparison to its conventional counterparts, including MPEG and H.26 x enabling a dramatically low cost encoder implementation. Side information generation, carried out at the decoder, is a major function in the DVC coding algorithm and plays a key-role in determining the performance of the codec. In this paper, a novel iterative refinement technique is proposed for the side information generation process. Simulation results of the proposed technique depict a consistent improvement in performance in comparison to the state-of-the-art in pixel domain DVC.

Multicast is an efficient paradigm for transmitting data from a sender to a group of receivers. According to the IEEE 802.11 standard, the multicast service is defined as an unreliable service, that is, it does not include the use of ACK frames. Furthermore, different to the unicast service, the multicast service makes use of a single rate out of the various rates included in the basic service set defined by the IEEE 802.11 standard. Even though various proposals have recently appeared in the literature addressing these issues, none of them has come out with a structured set of control mechanisms taking into account the varying conditions characterising the wireless channels as well as the requirements of various applications. A novel cross-layer auto rate selection multicast mechanism for multi-rate wireless LANs, namely auto rate selection for multicast, capable of adapting the data transmission to the varying conditions of the channel and taking into account the characteristics of various applications, is introduced. The simulation results show that our proposal outperforms the IEEE 802.11 standard and the mechanisms recently proposed in the literature.

Multicast video streaming over multirate wireless LANs imposes strong demands on video codecs and the underlying network. It is not sufficient that only the video codec or only the underlying protocols adapt to changes in the wireless link quality. Research efforts should be applied in both and in a synchronized way. Cross layer design is a new paradigm that addresses this challenge by optimizing communication network architectures across traditional layer boundaries. This paper presents cross-layer architecture for adaptive video multicast streaming over multirate wireless LANs where layer-specific information is passed in both directions, top-down and bottom-up. The authors jointly consider three layers of the protocol stack: the application, data link and physical layers. The authors analyze the performance of the proposed architecture and extensively evaluate it via simulations. The results show that the real-time video quality of the overall system can be greatly improved by cross-layer signaling.

Though H.264 is highly efficient compared to MPEG-2, the wide and deep penetration of MPEG-2 creates a need for co-existence of these technologies and hence creates a need for transcoding. In this paper, we introduce and evaluate a novel macroblock partition mode decision algorithm for inter-frame prediction to be used as part of a high-efficient MPEG-2 to H.264 transcoder. The proposed tools are used to compute an optimal MB coding mode decision with significantly reduced computational complexity. Specifically, we achieve the computational savings by using the following MB information coming from MPEG-2: the MB coding modes in MPEG-2 and the mean and variance of the 16 4×4 sub blocks of the MPEG-2 residual MBs. We use data mining algorithms to develop a decision tree for obtaining the H.264 coding decision modes. Our results show that the proposed algorithm is able to maintain a good picture quality while considerably reducing the number of operations to be performed.

In this paper, we introduce and evaluate a low complexity macroblock partition mode decision algorithm for inter-frame prediction in MPEG-2 to H.264 transcoder. The proposed tools are used to compute an optimal MB coding mode decision with significantly reduced computational complexity. Specifically, we achieve the computational savings by using the following MB information coming from MPEG-2: the MB coding modes, the coded block pattern (CBPC) in MPEG-2, and the mean and variance of the 16 4times4 sub blocks of the MPEG-2 residual MBs. We use data mining algorithms to develop a decision tree for H.264 coding mode decisions. The decision trees are built using RD optimized mode decisions and result in highly efficient mode decisions. The proposed transcoder is 35% faster than the RD optimized H.264 reference transcoder without a significant PSNR degradation. The proposed transcoder performs over 3 dB better than the SAE cost based H.264 transcoding

This paper presents a novel macroblock mode decision algorithm for inter-frame prediction based on machine learning techniques to be used as part of a very low complexity MPEG-2 to H.264 video transcoder. Since coding mode decisions take up the most resources in video transcoding, a fast macro block (MB) mode estimation would lead to reduced complexity. The proposed approach is based on the hypothesis that MB coding mode decisions in H.264 video have a correlation with the distribution of the motion compensated residual in MPEG-2 video. We use machine learning tools to exploit the correlation and derive decision trees to classify the incoming MPEG-2 MBs into one of the 11 coding modes in H.264. The proposed approach reduces the H.264 MB mode computation process into a decision tree lookup with very low complexity. The proposed transcoder is compared with a reference transcoder comprised of a MPEG-2 decoder and an H.264 encoder. Our results show that the proposed transcoder reduces the H.264 encoding time by over 95% with negligible loss in quality and bitrate.

The H.264 standard, jointly developed by the ITU-T and the MPEG committees, is highly efficient offering perceptually equivalent quality video at about 1/3 to 1/2 of the bitrates offered by the MPEG-2 format. These significant bandwidth savings open the market to new products and services, including HDTV services at lower bitrates. It is expected that the H.264/AVC takes over the digital video market, replacing the use of MPEG-2 in most digital video applications. The complete migration to the new video-coding algorithm takes several years given the wide scale use of MPEG-2 in the market place today. This creates an important need for transcoding technologies for converting the large volume of existent video material from the MPEG-2 into the H.264 format and vice versa. However, given the significant differences between the MPEG-2 and the H.264 encoding algorithms, the transcoding process of such systems is much more complex to other heterogeneous video transcoding processes. In this paper, we introduce and evaluate a novel fast intra-frame prediction algorithm to be used as part of a high-efficient MPEG-2 to H.264 transcoder. Our results show that the proposed algorithm is able to maintain a good picture quality while considerably reducing the number of operations to be performed.

MPEG-2 is the most widely digital video-encoding standard in use nowadays. It is being widely used in the development and deployment of digital TV services, DVD and video-on-demand services. However, recent developments have given birth to the H.264/AVC, offering better bandwidth to video quality ratios than MPEG2. It is expected that the H.264/AVC will take over the digital video market, replacing the use of MPEG-2 in most digital video applications. The complete migration to the new video-coding algorithm will take several years given the wide scale use of MPEG-2 in the market place today. This creates an important need for transcoding technologies for converting the large volume of existent video material from the MPEG-2 into the H.264 format and vice versa. However, given the significant differences between the MPEG-2 and the H.264 encoding algorithms, the transcoding process of such systems is much more complex to other heterogeneous video transcoding processes. In this paper, we introduce and evaluate a novel intra-frame prediction algorithm to be used as part of a high-efficient MPEG-2 to H.264 transcoder. Our evaluation results show that the proposed algorithm considerable reduces the complexity involved in the intra-frame prediction: a key operation in the transcoding process

HIPERLAN/2 is a recent standard from ETSI for highspeed wireless LANs. This work explores this standard when providing QoS support to different traffic types. We describe a new bandwidth allocation protocol, which distinguishes among five types of connections, each one of them having its own QoS requirements. We carry out a performance evaluation via simulations that reflects the behavior of the novel MAC protocol. The bandwidth allocation protocol is evaluated in terms of its flexibility and efficiency in supporting delay sensitive traffic. We look particularly to MPEG-4 video communications, an application which is expected to be widely deployed in broadband wireless LANs.

Personal communication systems (PCS) aim to provide ubiquitous service to its subscribers. In order to fulfil the ubiquity requirement for service, PCS rely on two main features: use of wireless communications technology and mobility management. The former sets the basis to untie subscribers from a wire allowing them to freely move around. The latter allows subscribers to gain access to the network services at all times regardless of their location. A handover is the process used to allow a call in progress to continue as the associated subscriber moves around. A large number of handover mechanisms have been reported in the literature. In this article, we carry out a comprehensive performance study of the handover mechanisms as proposed in the literature. A detailed simulation model has been developed allowing us to set up parameters such as the speed and motion path of the mobile terminal. The performance metrics of interest are: the length of the disruption time caused by the handover mechanism and the number of lost packets caused by the handover mechanism. Under the scenario under consideration, the handovers using multicasting mechanism and full reestablishment mechanism exhibit the best results.

Recent advances in wireless technology are enabling the design and deployment of multiservice wireless networks. In order to be able to meet the QoS requirements of the various applications, it is essential to deploy QoS provisioning mechanisms. In this paper, we present various QoS provisioning mechanisms. Our simulation results show the effectiveness of the mechanisms when supporting various types of services.

Recent advances on wireless technology are enabling the design and deployment of multiservice wireless networks. In order to be able to meet the QoS requirements of the various applications, it is essential to deploy QoS provisioning mechanisms. To be most effective, these mechanisms require to monitor the status of the various active sources enabling them to better distribute the available resources. We propose a QoS provisioning mechanism for time constrained applications. Our simulation results show the effectiveness of the proposed mechanism when supporting time constrained services, such as MPEG-4 video communications.

A large number of studies have been conducted to evaluate the benefits of using layered video coding schemes as a means to improve the robustness of video communications systems. In this article, we study a frame-aware layering scheme for the transport of DCT-based video over packet switched networks. Under this scheme, the relevance of the different elements of the video sequence is taken into account in order to compose the encoded video sequence. We conduct a detailed study over a large set of video streams encoded using the MPEG-2 video standard. Our results show that it is possible to reduce the video traffic while maintaining an acceptable video quality.

Two major issues in providing true end-to-end wireless/mobile video capabilities are: interoperability among network platforms and robustness of video compression algorithms in error-prone environments. In this paper, we mainly focus on the second issue and show how error resilience techniques can be used to improve the video quality. We argue that the error resilient tools provided within the MPEG-4 standard are not sufficient to provide acceptable quality in wireless/mobile networks, but that this quality can be significantly improved by the inclusion of hierarchical MPEG-4 video coding techniques. We present a novel hierarchical MPEG-4 video scheme particularly designed for video communications over QoS-capable wireless/mobile network.

MPEG-2 video communications over ATM networks is one of the most active research areas in the field of computer communications. In the transmission process of a variable bit rate video signal over an ATM network, cells are inevitably exposed to delays, errors, and losses due to the statistical multiplexing used in these networks. These phenomena affect the quality of the video signal, and without adequate measures to control the propagation of the impairments, the quality of the service may fall below acceptable levels. In this paper, we study the impact of cell losses on the quality of an MPEG-2 video sequence encoded in a variable bit rate mode. We introduce a set of control mechanisms at different levels of the protocol architecture to be used in MPEG-2-based video communications systems using ATM networks as their underlying transmission mechanism. Our results (using different video sequences) show the effectiveness to improve the video quality by using a structured set of control mechanisms to overcome for the loss of cells carrying VBR MPEG-2 video streams. We argue that in order to be able to create video systems able to cope with cell losses encountered in computer communications systems, a structured set of error-resilient protocol mechanisms is needed.

We introduce a set of control mechanisms at different levels of the protocol architecture to be used in MPEG-2-based video communications systems using ATM networks as their underlying transmission mechanism. Our results show the effectiveness of using a structured set of control mechanisms to overcome for the loss of cells carrying VBR video streams.

MPEG-2 video communications over ATM networks is one of the most active research areas in the field of computer communications. In this paper, we introduce a set of control mechanisms at different levels of the protocol architecture to be used in MPEG-2-based video communications systems using ATM networks as their underlying transmission mechanism. We argue that in order to be able to create video systems able to cope with some of the errors encountered in computer communications systems, a structured set of error-resilient protocol mechanisms is needed. Our results show the effectiveness of using a structured set of control mechanisms to overcome for the loss of cells carrying VBR MPEG-2 video streams.

We propose the implementation of a MPEG encoder developed by the University of California at Berkeley on a multicomputer system. Since this application is in real time, we present a mapping of the video sequence between the EPs of the architecture, where the communication between EPs is minimized. We also propose the necessary load/store process with a simple mechanism input/output, where the global distribution process latency is compensated. Idonety of the topology of the system is analyzed, together with the most adequate commutation technique for the interconnection network. Finally the incidence of the frame format on the system communication performance is analyzed.