Common representations of light fields use four-dimensional data structures, where a given pixel is closely related not only to its spatial neighbours within the same view, but also to its angular neighbours, co-located in adjacent views. Such structure presents increased redundancy between pixels, when compared with regular single-view images. Then, these redundancies are exploited to obtain compressed representations of the light field, using prediction algorithms specifically tailored to estimate pixel values based on both spatial and angular references. This paper proposes new encoding schemes which take advantage of the four-dimensional light field data structures to improve the coding performance of Minimum Rate Predictors. The proposed methods expand previous research on lossless coding beyond the current state-of-the-art. The experimental results, obtained using both traditional datasets and others more challenging, show bit-rate savings no smaller than 10%, when compared with existing methods for lossless light field compression.

A common approach used in omnidirectional video coding is based on frame splitting into tiles, allowing partial delivery of only the subset of tiles that is necessary to render the user’s current viewing region, defined as a specific viewport or Field-of-View (FoV). Since tiles can be independently encoded, such mechanism provides a flexible solution for encoding planar representations with ultra-high definition (UHD), such as the Equirectangular Projection (ERP), using Versatile Video Coding (VVC). By only selecting and transmitting the coded data that is required to render the necessary FoV, rather than the full 360°, a great deal of bandwidth can be saved. While current solutions are based on splitting the omnidirectional video frames into tiles of equal size, this paper proposes a new approach based on adaptive tile size, driven by visual attention. Those regions where the visual attention is higher are partitioned in smaller tiles to obtain higher bit rate granularity, allowing to decode the most frequent FoVs with minimum out-of-FoV pixels and reduced bandwidth. Optimal tile boundaries are found by solving a lagrangian minimisation problem with a cost function that achieves the best tradeoff between the standard deviation and the average attention-weighted bit rate per tile. The experimental results show that an average of 7.17% and 17.73% of bit rate savings is obtained in comparison with conventional tilling methods for the commonly used FoVs of $90^{\circ} \times 90^{\circ}$ and $45^{\circ} \times 45^{\circ}$, respectively.

Encoding 360° video with ultra high spatial resolution requires high bitrates to guarantee acceptable QoE in video delivery services. However, since in general the full Field-of-View (FoV), i.e., 360°, is not required at once, a great deal of bandwidth can be saved if only a limited FoV is delivered, according to content relevancy or/and user demand. This work addresses this problem using the concept of Adaptive Resolution Change (ARC) defined in the forthcoming Versatile Video Coding (VVC) standard, by dynamically mapping the full FoV into multiple video frames with different spatial resolutions. Those FoVs attracting more visual attention are encoded with higher resolution while the others are encoded with lower resolution, thus without compromising the visual quality and resolution of the most relevant regions. The simulation results show that the proposed adaptive coding scheme is able to deliver high quality video for the most relevant FoV at any time instant, achieving a maximum bitrate reduction of 37.2%.

This paper describes a robust depth estimation algorithm for multi-focus plenoptic images. The main feature of the proposed method consists of a hybrid template matching scheme built-upon intensity and local phase information, which adapts to the blurriness of neighbouring lenslet microimages. By reducing the impact of defocusblur on the template matching accuracy, the proposed method efficiently handles the varying triangulation baseline over the depth-of-field, thus discarding the need for scene-related information such as the expected range of disparities. Experimental results demonstrate the robustness of the proposed method over the most used commercially available depth estimation algorithm, achieving a reduction of 73% on the depth estimation error.

Efficient light field encoders take advantage of the inherent 4D data structures to achieve high compression performance. This is accomplished by exploiting the redundancy of co-located pixels in different sub-aperture images (SAIs) through prediction and/or transform schemes to find a m ore compact representation of the signal. However, in image regions with higher disparity between SAIs, such scheme's performance tends to decrease, thus reducing the compression efficiency. This paper introduces a reversible pre-processing algorithm for disparity compensation that operates on the SAI domain of light field data. The proposed method contributes to improve the transform efficiency of the encoder, since the disparity-compensated data presents higher correlation between co-located image blocks. The experimental results show significant improvements in the compression performance of 4D light fields, achieving Bjontegaard delta rate gains of about 44% on average for MuLE codec using the 4D discrete cosine transform, when encoding High Density Camera Arrays (HDCA) light field images.

This letter proposes a method to obtain integer reversible discrete cosine transforms for generic transform-based coding schemes. The novelty of the proposed method, which is based on decomposition of the DCT-II matrix into two triangular and one diagonal matrices, is twofold: (i) the new matrices can be of arbitrary size, i.e., any square N × N dimension, thus suitable for applications where non power-of-2 dimensions are required; (ii) they can be designed with adjustable precision in a trade-off with the number of representation bits. Furthermore, improvements are also proposed over the base scheme to avoid numerical issues when working with large matrices and to obtain more reliable approximations. The performance evaluation demonstrate the effectiveness of the proposed transforms to approximate the coding gain capabilities of the original DCT-II.

This paper presents a method to improve the lossless compression efficiency of light field encoding based on Minimum Rate Predictors (MRP). The proposed method relies on the use of multiple references, either micro-images or sub-aperture images, to provide a richer set of correlated pixels for prediction. The results show better compression ratios than conventional versions of MRP, for both representation formats (micro-image and sub-aperture image arrays), achieving gains ranging from 16.9% to 21.2%. Furthermore, it is also shown that the proposed method consistently outperforms the state-of-the-art lossless encoders HEVC and JPEG-LS.

High quality omnidirectional video requires ultra high resolution formats encoded with very high bit rates to guarantee acceptable QoE in video delivery services. Since in general the full FoV, i.e., 360°, is not required at once by users, rather than agnostic encoding of the whole 360° video, this work proposes a flexible coding approach where the full FoV is mapped into video frames and efficiently encoded using intra-FoV prediction. By avoiding inter-FoV prediction, the proposed approach enables independent decoding of one or more FoVs extracted from a single compressed stream containing the full FoV video. To achieve improved quality in those FoVs which attract more visual attention, non-uniform coding is proposed for the new Versatile Video Coding standard (VVC), using perceptually-driven quantisation for each FoV. This strategy, makes use of visual attention maps to decrease the overall bit rate without compromising the quality of the most relevant regions. The simulation results show that the proposed coding mechanism achieves consistent quality gains in the relevant FoV without significant losses in the remaining ones. In comparison with the reference VVC, the proposed method is able to achieve average quality gains up to 1.56 dB and to efficiently adapt the coding parameters to the visual attention information.

This paper presents a method to improve disparity maps computed from light field images using structure tensor methods, which tend to expand the borders of the occluding objects, enlarging their silhouette. The proposed method relies on the fact that such regions of the silhouette are defined by a mismatch between the disparity map edges, computed by the structure tensor, and those of the corresponding epipolar plane images (EPI) representing the light field. The proposed silhouette improvement method determines a correspondence between EPI edges and the disparity map edges, identifying the erroneous silhouette regions. The disparity map is corrected by using neighbouring values computed with high structure tensor reliability. The achieved results show that the disparity map is improved both around object edges and overall, reducing the MSE by 47.9% in comparison with other methods also based on the structure tensor.

The performance of focus metrics in the evaluation of refocused images from light fields is investigated in this paper. To this aim, the paper presents a comprehensive study on the performance of a large set of different focus metrics (34 in total) in the evaluation of patch-based extended depth-of-field reconstructed images (e.g., all-in-focus). The new findings of this work demonstrate that optimal reconstruction of extended depth-of-field images, from light fields captured with focused plenoptic cameras, is not consistent with the focus level figures computed by available focus metrics. The results show that a higher focus level, as given by such computational methods, does not actually correspond to better all-in-focus images, thus indicating that currently available focus metrics are not suitable for evaluating the quality of extended depth-of-field reconstruction. The results obtained through subjective evaluation confirm that objective focus metrics fail to indicate the best focused images. Finally, the paper presents recommendations to adapt existing metrics to extended depth-of-field reconstruction in plenoptic imaging.

The increased compression ratios achieved by the High Efficiency Video Coding (HEVC) standard lead to reduced robustness of coded streams, with increased susceptibility to network errors and consequent video quality degradation. This paper proposes a method based on a two-stage approach to improve the error robustness of HEVC streaming, by reducing temporal error propagation in the case of frame loss. The prediction mismatch that occurs at the decoder after frame loss is reduced through the following two stages. First, at the encoding stage, the reference pictures are dynamically selected based on constraining conditions and Lagrangian optimization, which distributes the use of reference pictures, by reducing the number of prediction units that depend on a single reference. Second, at the streaming stage, a motion vector (MV) prioritization algorithm, based on spatial dependencies, selects an optimal subset of MVs to be transmitted, redundantly, as side information to reduce mismatched MV predictions at the decoder. The simulation results show that the proposed method significantly reduces the effect of temporal error propagation. Compared with the reference HEVC, the proposed reference picture selection method is able to improve the video quality at low-packet-loss rates (e.g., 1%) using the same bitrate, achieving quality gains up to 2.3 dB for 10% of packet loss ratio. It is shown, for instance, that the redundant MVs are able to boost the performance achieving quality gains of 3 dB when compared with the reference HEVC, at the cost using 4% increase in total bitrate.

The emergence of 3D video technologies and their foreseeable applications in Internet Protocol Television (IPTV) and video delivery systems using encoded 3D video contents over packet networks raises the question of how to manage the Quality of Experience (QoE) across diverse lossy channels. Of particular importance for QoE management is the problem of measuring the impact of data losses in packetized 3D video information and how it affects the quality experienced by end users, when the content is rendered and presented at their premises. Previous work by the authors showed that it is possible to model the perceived quality degradations through the use of artificial neural networks receiving as inputs several parameters describing the packet loss events. The first stage of such model was specifically developed for packetized 3D video in texture-plus-depth format where only the depth information was prone to transmission errors. This article presents an extension of the previous model by including the effect of texture information losses along with other specific aspects associated with the dual nature of this type of data loss. The validity of the model is verified through the use of extensive simulations and comparisons between real and estimated values of a recently proposed 3D video quality measure.

In this paper a robust encoding scheme is proposed to improve the visual quality of HEVC decoded video when intra frames are lost along the streaming path. For this purpose, the encoding process includes frame loss simulation and subsequent error concealment, to find the most efficient method that should be used by a decoder to recover lost intra frames. In this novel scheme, each image is divided into partitions, which are associated with the error concealment method that achieves the lowest distortion. Then this information is signalled to the decoder through SEI messages in the coded stream. In order to efficiently use the signalling overhead, rate-distortion optimisation is used to achieve the best trade-off between the number of transmitted symbols and distortion of reconstructed frames. Experimental results show the effectiveness of the proposed method to enhance the quality of reconstructed intra frames under different packet loss ratios (PLR). For PLR=10%, the robust coding scheme is able to improve the average PSNR of all frames affected by errors, up to 1.50 dB and 3.44 dB in Low-Delay and Random-Access configurations respectively, at a maximum overhead cost of 0.24%.

Several different methods have been investigated in recent years, aiming at computational complexity reduction and scaling of High Efficiency Video Coding (HEVC) software implementations. However, maintaining the encoding time per frame or group of pictures (GOPs) below an adjustable upper bound is still an open research issue. A solution for this problem is devised in this paper based on a set of Pareto-efficient encoding configurations, identified through rate-distortion-complexity analysis. The proposed method combines a medium-granularity encoding time control with a fine-granularity encoding time control to accurately limit the HEVC encoding time below a predefined target for each GOP. It is shown that the encoding time can be kept below a desired target for a wide range of encoding time reductions, e.g., up to 90% in comparison with the original encoder. The results also show that compression efficiency loss (Bjøntegaard delta-rate) varies from negligible (0.16%) to moderate (9.83%) in the extreme case of 90% computational complexity reduction.

Efficient computation of visual saliency regions has been a research problem in the recent past, but in the case of 3D content no definite solutions exist. This paper presents a computational method to determine saliency regions in 3D video, based on fusion of three feature maps containing perceptually relevant information from spatial, temporal and depth dimensions. The proposed method follows a bottom-up approach to predict the 3D regions where observers tend to hold their gaze for longer periods. Fusion of the feature maps is combined with a center-bias weighting function to determine 3D visual saliency map. For validation and performance evaluation, a publicly available database of 3D video sequences and corresponding fixation density maps was used as ground-truth. The experimental results show that the proposed method achieves better performance than other state-of-art models.

The improved compression efficiency of High Efficiency Video Coding (HEVC) comes with large increases in computational complexity, which has been lately dealt by researchers with complexity reduction and scaling methods. However, encoding time control at frame or Group of Pictures (GOP) level is still an open issue that must be investigated. In this work, a Rate-Distortion-Complexity analysis is performed upon a set of configurations that have been created based on findings and techniques of previous works. The proposed control system uses the best 27 configurations to adjust the encoding time per GOP and yields encoding time reductions of up to 84.5% with an average difference between target and encoding times of 4.1%.

The improved compression efficiency achieved by the High Efficiency Video Coding (HEVC) standard has the counter-effect of decreasing error resilience in transmission over error-prone channels. To increase the error resilience of HEVC streams, this paper proposes a checkerboard reference picture selection method in order to reduce the prediction mismatch at the decoder in case of frame losses. The proposed approach not only allows to reduce the error propagation at the decoder, but also enhances the quality of reconstructed frames by selectively constraining the choice of reference pictures used for temporal prediction. The underlying approach is to increase the amount of accurate temporal information at the decoder when transmission errors occur, to improve the video quality by using an efficient combination of diverse motion fields. The proposed method compensates for the small loss of coding efficiency at frame loss rates as low as 3%. For a single frame-loss event the proposed method can achieve up to 2 dB of gain in the affected frames and an average quality gain of 0.84 dB for different error prone conditions.

The High Efficiency Video Coding standard provides improved compression ratio in comparison with its predecessors at the cost of large increases in the encoding computational complexity. An important share of this increase is due to the new flexible partitioning structures, namely the coding trees, the prediction units, and the residual quadtrees, with the best configurations decided through an exhaustive rate-distortion optimization (RDO) process. In this paper, we propose a set of procedures for deciding whether the partition structure optimization algorithm should be terminated early or run to the end of an exhaustive search for the best configuration. The proposed schemes are based on decision trees obtained through data mining techniques. By extracting intermediate data, such as encoding variables from a training set of video sequences, three sets of decision trees are built and implemented to avoid running the RDO algorithm to its full extent. When separately implemented, these schemes achieve average computational complexity reductions (CCRs) of up to 50% at a negligible cost of 0.56% in terms of Bjontegaard Delta (BD) rate increase. When the schemes are jointly implemented, an average CCR of up to 65% is achieved, with a small BD-rate increase of 1.36%. Extensive experiments and comparisons with similar works demonstrate that the proposed early termination schemes achieve the best rate-distortion-complexity tradeoffs among all the compared works.

This paper addresses the problem caused by motion vector coding dependencies on the error resilience performance of the emergent High Efficiency Video Coding (HEVC) standard. We propose a method based on the prediction dependency of motion vectors (MV) to select the most relevant ones for redundant coding with reduced overhead. The spatial dependencies are analysed in the encoder to prioritise the MVs that should be selected for redundancy, based on the number of subsequent dependent coding units. Then, a subset of prioritised MVs is transmitted as redundancy (referred to as side information in the paper), to reduce the use and propagation of mismatched MV predictions in case of transmission errors or data loss. The simulation results show that the proposed MV selection method can effectively identify the most relevant motion field, achieving improved error robustness with a reduced redundancy overhead. Exploiting only 30% of the generated MVs for redundancy, average quality gains of up to 1 dB are achieved compared to a uniform MV selection scheme, and up to 2 dB compared to the original HEVC standard with no redundant encoded information.

A no-reference (NR) method based on an artificial neural network (ANN) approach is proposed in this paper to estimate the objective quality of video-plus-depth streams subject to packet loss in depth data. A novel aspect of this method is the use of information only taken from packet headers, up to the network abstraction layer (NAL), requiring a very low complexity parsing of the compressed video streams. A maximum of seven packet-layer parameters were found to be enough to provide accurate objective quality estimates given by the structural similarity index (SSIM). The accuracy of the quality estimates, evaluated by comparison with the actual SSIM quality scores, is shown to be sufficiently high (e.g., Pearson Linear Correlation Coefficient over 0.92) for lightweight implementations of 3D video quality monitors at end-user receivers and also at network nodes.

The flexible encoding structures of High Efficiency Video Coding (HEVC) are the main responsible for the improvements of the standard in terms of compression efficiency in comparison to its predecessors. However, the flexibility provided by these structures is accompanied by high levels of computational complexity, since more options are considered in a Rate-Distortion (R-D) optimization scheme. In this paper, we propose a four-step early-termination method, which decides whether the inter mode decision should be halted without testing all possibilities. The method employs a set of decision trees, which are trained offline once, using information from unconstrained HEVC encoding runs. The resulting trees present a mode decision accuracy ranging from 97.6% to 99.4% with a negligible computational overhead. The method is capable of achieving an average computational complexity decrease of 49% at the cost of a very small Bjontegaard Delta (BD)-rate increase (0.58%).

The emerging HEVC standard introduces a number of tools which increase compression efficiency in comparison to its predecessors at the cost of greater computational complexity. This paper proposes a complexity control method for HEVC encoders based on dynamic adjustment of the newly proposed coding tree structures. The method improves a previous solution by adopting a strategy that takes into consideration both spatial and temporal correlation in order to decide the maximum coding tree depth allowed for each coding tree block. Complexity control capability is increased in comparison to a previous work, while compression losses are decreased by 70%. Experimental results show that the encoder computational complexity can be downscaled to 60% with an average bit rate increase around 1.3% and a PSNR decrease under 0.07 dB.

This paper deals with reconstruction of corrupted depth maps received by multiview video-plus-depth (MVD) decoders from error prone channels. An interview-based method is proposed using warping vectors obtained through a block matching approach with geometric transforms (BMGT) between two colour views. It is shown that BMGT is able to find efficient warping vectors for reconstruction of lost regions in the depth maps associated with the colour views. The proposed concealment method uses an additional contour reconstruction technique, applied to arbitrary shapes within the lost regions, which is used for weighted interpolation. In comparison to a reference method based on simple weighted interpolation, the proposed method is able to achieve PSNR gains in synthesised views up to 5.61 dB, at data loss ratios up to 40%.

The High Efficiency Video Coding standard shows improved compression efficiency in comparison to previous standards at the cost of higher computational complexity. In this paper, a complexity scalability method for HEVC encoders based on the dynamic adjustment of the number of constrained coding treeblocks is proposed. The method limits the Prediction Unit shapes and the maximum tree depth used in each Coding Treeblock in order to decrease the number of evaluations performed in the Rate-Distortion Optimization process. The encoder is capable of trading off computational complexity and compression efficiency while still maintaining the encoding time per Group of Pictures (GOP) under a pre-defined target. The encoding complexity can be decreased in up to 60% when compared to the original encoder at the cost of small Bjontegaard Delta (BD)-rate increases.

The recently introduced quadtree coding structures used in HEVC increase compression efficiency in comparison to previous standards at the cost of higher computational complexity levels. This paper proposes an evolution of a complexity control method for HEVC encoders based on the dynamic adjustment of these structures' maximum depth. The new method improves the previous solution by adopting a new control strategy and compensating the motion effect on a maximum tree depth map which is central to the complexity control strategy. The proposed method is capable of performing a more accurate complexity control than our previous strategy while still reducing compression efficiency losses in terms of image quality and bit rate.

The emerging HEVC standard introduces several techniques which increase compression efficiency in comparison to its predecessors. However, such advances are accompanied by increases in computational complexity, limiting the encoder use in computational or power-constrained devices. This paper proposes a novel complexity control method for the future HEVC encoders based on a dynamic adjustment of the newly proposed coding tree structures. The relationship between coding tree depths and the encoding complexity is explored to selectively constrain encoding possibilities in order to not exceed a predefined complexity target. Experimental results show that the encoder computational complexity can be downscaled to 60% with a bit rate increase under 3.5% and a PSNR decrease under 0.1 dB.

This paper presents a method to recover lost blocks in depth maps affected by data loss in 3D image/video communications over error prone networks. The proposed method relies on the color image for accurate reconstruction of the lost contour segments in the corresponding depth map areas. Such reconstructed depth map contours are then used as boundaries at different depth planes to recover the missing depth values through weighted interpolation. The method performance is evaluated by the objective quality (PSNR) of the synthesised views. Images decoded with the reconstructed depth maps are compared with those of the reference method. The proposed method exhibits PSNR gains up to 1.49dB higher than the reference one, and a better performance is consistently achieved for different 3D image content.

This paper presents a performance evaluation study of coding efficiency versus computational complexity for the forthcoming High Efficiency Video Coding (HEVC) standard. A thorough experimental investigation was carried out to identify the tools that most affect the encoding efficiency and computational complexity of the HEVC encoder. A set of 16 different encoding configurations was created to investigate the impact of each tool, varying the encoding parameter set and comparing the results with a baseline encoder. This paper shows that, even though the computational complexity increases monotonically from the baseline to the most complex configuration, the encoding efficiency saturates at some point. Moreover, the results of this paper provide relevant information for implementation of complexity-constrained encoders by taking into account the tradeoff between complexity and coding efficiency. It is shown that low-complexity encoding configurations, defined by careful selection of coding tools, achieve coding efficiency comparable to that of high-complexity configurations.

This paper extends the current concept of multiple description coding (MDC) to the compressed domain, by proposing efficient splitting of standard single description coded (SDC) video into a multi-stream representation. A novel multiple description video splitting (MDVS) scheme is proposed to operate at network edges, for increased robustness in path diversity video streaming across heterogeneous communications chains. It is shown that poor performance of existing methods is mainly due to distortion accumulation, i.e., drift, when decoding is carried out with missing descriptions. The proposed scheme is able to effectively control drift distortion in both intra and inter predictive coding, even when only one description reaches the decoder. This is achieved by generating a controlled amount of relevant side information to compensate for drift accumulation, whenever any description is lost in its path. The simulation results show that any individual description can be decoded on its own without producing drift, achieving significant quality improvement at reduced redundancy cost. The overall performance evaluation, carried out by simulating video streaming over lossy networks with path diversity, also demonstrates that MDVS enables higher quality video in such heterogeneous networking environments, for a wide range of packet loss rates.

This paper proposes a method to recover lost regions in image-based depth maps used in video plus depth 3D format. This method performs depth maps reconstruction taking into account depth contours within the lost regions. This is achieved by extracting the contours and recovering their lost segments based on Bézier curve fitting, followed by spatial interpolation. The proposed method maintains contour smoothness and uses them as the boundary limits of homogeneous depth regions, which are then filled through weighted pixel interpolation. The experimental results show that the proposed method yields better synthesized images than classic spatial concealment methods, uniquely based on pixel interpolation techniques. The method presented in this paper is able to outperform the reference method, in terms of PSNR by up to 1.91dB. The subjective quality is also shown as being significantly better.

This paper proposes a method to efficiently find motion vector predictions for zonal search motion re-estimation in fast video transcoders. The motion information extracted from the incoming video stream is processed to generate accurate motion vector predictions for transcoding with reduced complexity. Our results demonstrate that motion vector predictions computed by the proposed method outperform those generated by the highly efficient EPZS (Enhanced Predictive Zonal Search) algorithm in H.264/AVC transcoders. The computational complexity is reduced up to 59.6% at negligible cost in R-D performance. The proposed method can be useful in multimedia systems and applications using any type of transcoder, such as transrating and/or spatial resolution downsizing.

This paper investigates the subjective impact resulting from different concealment methods for coping with lost frames in 3D video communication systems. It is assumed that a high priority channel is assigned to the main view and only the auxiliary view is subject to either transmission errors or packet loss, leading to missing frames at the decoder output. Three methods are used for frame concealment under different loss ratios. The results show that depth is well perceived by users and the subjective impact of frame loss not only depends on the concealment method but also exhibits high correlation with the disparity of the original sequence. It is also shown that under heavy loss conditions it is better to switch from 3D to 2D rather than presenting concealed 3D video to users.

This paper proposes a multiple description (MD) transcoding scheme capable of preventing drift by distortion accumulation in temporally predicted motion compensated slices. Drift compensation is achieved by generating a controlled amount of side information to be used for decoding whenever a description fails to reach the end user terminal. The side information is generated by re-encoding the transcoding residue with an independent quantisation parameter which also controls redundancy. A simplified architecture is devised to reduce transcoding complexity in regard to the number of processing functions and buffer requirements. The experimental results show that temporally predicted frames do not suffer from drift and their quality is significantly improved at reduced redundancy cost in comparison with a classic MD transcoding scheme.

This paper proposes a multiple description coding scheme based on a multi-loop structure, which prevents drift distortion accumulation in intra predicted slices. The drift is compensated by generating a controlled amount of side information used by the decoder whenever any description is lost in the corresponding network path. The experimental results show that intra predicted slices do not suffer from drift and their quality is significantly improved (e.g., 6–8 dB) at reduced redundancy cost, (e.g., 0.2–0.25), in comparison with the open loop implementation. Error propagation in subsequent frames is also evaluated when one description is lost for a whole frame and for two rows of macroblocks. In both cases the overall video quality is significantly improved and considering normal GOP sizes the redundancy introduced by the proposed scheme is negligible.

This paper deals with conversion from H.264/AVC (advanced video coding) coded video into the MPEG-2 format. The proposed approach exploits similarities between the coding techniques used in both standards in order to achieve a computationally efficient method for transcoding interframe coded slices. The conversion process is based on adaptation of both coding mode and motion information embedded in the H.264/AVC video stream, such that subsequent MPEG-2 encoding takes full advantage of the higher computational effort spent on the first encoding step. The proposed transcoding scheme significantly reduces the computational complexity needed for MPEG-2 interframe coding by reusing relevant information from the H.264 bitstream. The simulation results show that computational complexity savings up to 60%, with a marginal objective quality cost, can be achieved in comparison with a cascaded decoder-encoder.

The work presented in this poster reflects the first results drawn from the implementation of the MulE Game Engine, an open-source architecture implemented to develop realistic MMORPGs.

Mobile access to multimedia contents requires video transcoding functionality at the edge of the mobile network for interworking with heterogeneous networks and services. Under hard transcoding conditions, the bandwidth of a coded video stream needs to be drastically reduced such that the original temporal resolution cannot be maintained. Thus consecutive frame skipping is often unavoidable at the transcoder. We propose an efficient mechanism for improving the quality of service (QoS) delivered to the mobile user, by minimising consecutive frame skipping in transcoding systems. The simulation results show that a better signal quality is obtained at the receiver during hard transcoding periods.

The performance of various cellular planning methods that decrease co-channel interference in GSM without sacrificing traffic capacity is evaluated. The advantages of each method are measured by calculating the carrier-to-interference ratio, C/I, the use of different clusters and the benefits of sectorisation being studied. An evaluation of the influence of frequency hopping on C/I is also done. The multiple re-use patterns method (MRP) is investigated as well, and a comparison is performed with previous results. The results show that changing the cluster size from 4 to 3 leads to a decreases in C/I of 2.6 dB. Several real antennas are studied for sectorisation, the best results being obtained for the 90/spl deg/ beamwidth one. The use of sectorisation, together with MRP, allows an increase in network performance, without visible additional costs.

In video distribution services, various networks of different capacity may be linked together to form the branches of a multicasting tree. In order to efficiently use the available bandwidth of each subnetwork, a video transcoder capable of reducing the bit rate of the incoming bit stream must be used at those nodes whose output links have less bandwidth than the input one. In this paper, we analyze the buffering implications of inserting a video transcoder within the transmission path. For transcoders with either fixed or variable compression ratio, we show that the encoder buffer size can be maintained as if no transcoder existed while the decoder has to modify its own buffer size according to both the bit rate conversion ratio and transcoder buffer size. We derive the conditions that have to be met by both the encoder and transcoder buffers for preventing the decoder buffer from underflowing or overflowing. Furthermore, based on the characteristics of constant bit rate (CBR) MPEG coded video, we show that efficient bit rate control can be implemented in CBR video transcoders such that the picture quality of transcoded sequences is practically the same as those directly encoded from the original sequence at the same reduced bit rates.

We propose a bit rate control algorithm for video transcoding, based on a dynamic buffer strategy. We show that the bit rate reduction ratio used for transcoding CBR bit streams should not follow the constant relation given by the input and output channel capacities but follow a variable function dependent upon the picture type instead. Based on a simulation study, the influence of the dynamic buffer occupancy on the picture quality is discussed and the proposed algorithm is shown to be capable of achieving transcoded picture quality comparable to that of single-stage encoding.

Many of the forthcoming video services and multimedia applications are expected to use preencoded video for storage and transmission. Video transcoding is intended to provide transmission flexibility to preencoded bit streams by dynamically adjusting the bit rate of these bit streams according to new bandwidth constraints that were unknown at the time of encoding. In this paper, we propose a drift-free MPEG-2 video transcoder, working entirely in the frequency domain. The various modes of motion compensation (MC) defined in MPEG-2 are implemented in the discrete cosine transform (DCT) domain at reduced computational complexity. By using approximate matrices to compute the MC-DCT blocks, we show that computational complexity can be reduced by 81% compared with the pixel domain approach. Moreover, by using a Lagrangian rate-distortion optimization for bit reallocation, we show that optimal transcoding of high-quality bit streams can produce better picture quality than that obtained by directly encoding the uncompressed video at the same bit rates using a nonoptimized Test Model 5 (TM5) encoder.

Video transcoding techniques offer the possibility of matching coded video to transmission channels of lower capacity by reducing the bit rate of compressed bit streams. In this paper we propose a new frequency domain video transcoder for bit rate reduction of compressed bit streams. A motion compensation (MC) loop, operating in the frequency domain, is used for drift compensation at reduced computational complexity. We derive approximate matrices for fast computation of the MC blocks in the frequency domain. By using the Lagrangian optimisation in calculating the best quantiser scales for transcoding, we show that transcoded pictures from a high quality bit stream are better than those encoded from original frames at the same reduced bit rates.

In this paper, video transcoding is introduced as a mechanism capable of decoupling video encoders from network constraints. A video transcoder is proposed for congestion control of pre-encoded video traffic over asynchronous transfer mode (ATM) networks and to provide flexible transmission in video distribution applications. It is shown that as long as the network delay does not exceed the equivalent multiplex buffer capacity, traffic can be efficiently controlled to ease congestion. It is also shown that video distribution over heterogeneous networks can use transcoders for providing fairness among users of the same transmission tree.

Transcoding is regarded as a down conversion process, where the bit rate of a compressed video bit stream is reduced according to a given constraint. Based on a transcoding architecture, previously developed by the authors, an optimal transcoder in a rate-distortion sense is proposed. It is shown that the basic architecture provides the necessary support for measuring the global transcoding distortion to be minimised under the optimisation algorithm. The experimental results show that, optimally transcoded pictures have a better quality than those encoded from the original video material, using a standard encoder at the same bit rates. This paper shows that compressed video can be further compressed with a good efficiency.

It is expected that most of the video services will be based on the MPEG2 standard and many of them using recorded streams. When compressed video is recorded, the characteristics of the channel through which it will be transmitted are assumed to be known beforehand. Therefore a great lack of flexibility arises in transmission of these streams when channels of diverse characteristics are used. If the same video programme is to be simultaneously distributed to several users through channels with different capacities, the service provider needs to keep several copies of that programme, each one encoded according to the corresponding channel characteristics. We show that it is only required to keep one copy of the coded data at its highest possible quality. Transcoding the main stream to lower rates is achieved with minimum delay. Therefore the transcoder is also capable of fast response to network demands to prevent packet loss.

Variable bit rate traffic generated by multimedia and video services may experience cell loss when transmitted over ATM networks. In a video distribution environment, where several links with different capacities are employed, it is likely to find nodes with less capacity than the offered traffic by the distributed bit stream. Either high cell loss rate should be allowed at these nodes or the source has to comply with the higher constraint penalising other users. We present a generic congestion control scheme capable of being used with either type of MPEG-2 video sources, real-time encoders or video servers. The scheme is based on a low delay post-processing mechanism capable of reducing the bit rate of an encoded bit stream without drift. Its application in video distribution and congestion control is presented. The results show good performance in all cases.

A video codec based on several parallel digital signal processors is described. The digital signal processors (DSPs) can be easily programmed to implement the H.261 algorithm and are organized as a single instruction multiple data (SIMD) computing architecture. Both the encoder and the decoder divide a picture in regions of horizontal strips and use one local processor per region. These local processors code (decode) one horizontal strip of data which, using the terminology of the H.261 standard, corresponds to two group of blocks (GOBs). They also communicate to a central processor which multiplexes (demultiplexes) the coded data from (for) the processors in the encoder (decoder). In the case of the encoder the central processor also controls a data buffer for bit-rate adaptation. Lateral communication between adjacent processors is implemented to allow comparisons between blocks situated in neighbouring regions, as required by most motion estimation algorithms.