While many recent international video coding standards, especially H.264/MPEG-4 AVC, leverage block size adaptivity in motion estimation, the rate-distortion boundary can be pushed further by allowing even more freedom in the partitioning process of inter pictures. Adaptive-shape partitioning, which allows blocks to be partitioned along a straight line that runs through the block at a freely chosen angle and position, complements the regular subblock partitioning, allowing the encoder to better adapt to the local characteristics of the motion activity in a video sequence. However, the technique demands excessive encoder resources to exhaust the large search space. This paper is the result of an investigation into the relative rate-distortion importance of the various adaptive-shape modes, both in terms of the angle of the partition boundary and of its location within a block. We find that a significant reduction of the search space with a factor of up to 40 can be accomplished, while retaining 50 to 90% of the compression gain obtained in the state of the art. This allows encoders to operate at much lower complexity levels and also reduces the signaling overhead associated with adaptive-shape partitioning. Based on our observations, we formulate a number of approaches to trade off compression performance against encoder complexity. Furthermore we discuss the use of various schemes of overlapping motion estimation along the partition boundary, an aspect which is currently left unaddressed in the literature on adaptive-shape partitioning. We introduce the use of shape-adaptive transforms for the motion compensated signal, to avoid the condition that arises with adaptive-shape partitioning where a partition boundary lies inside a transform block. The result is a reduction in ringing artifacts while maintaining objective quality.

In this paper, we discuss motion-refined rewriting of single-layer H.264/AVC streams to SVC streams with multiple quality layers. First, we elaborate on techniques we developed for efficient rewriting of residual data from H.264/AVC to SVC. We investigate if rate-distortion performance can further be improved by extending these architectures with motion refinement techniques, which exploit the inter-layer motion prediction mechanisms available in SVC. For optimum performance, we discuss a fast rate-distortion technique based on Lagrangian relaxation. Although motion refinement in the transform-domain leads to extra distortion in the bitstream, we show that our rate-distortion model successfully takes into account both base and enhancement layer rate and distortion during optimization. Implementation results show that motion-refined rewriting in the transform domain can increase rate-distortion performance, with gains of up to 0.5dB for the SVC base layer. The presented rewriting architectures significantly reduce the computational complexity when compared to reencoding, with a speed-up by a factor of forty or more, even in the case of motion refinement.

Mastitis is a major infectious disease affecting high yielding cows in dairy herds. Because of its economic impact and due to the animal welfare policy, the pathogenesis of this intramammary infection was studied extensively over the past 50 years. Still, the costs associated with the use of dairy cows for mastitis research constitute a major drawback. As an alternative, a mouse model of experimentally induced mastitis was developed some decades ago. This model has been increasingly used as it appears to be very suited for studying ruminant mastitis due to similarities between mice and cows. The various techniques for inducing mastitis in mice as well as the different pathogens and initial inoculum doses used are also compared in this review. Moreover, recent findings concerning the administration of antimicrobial and immunomodulatory agents are discussed. In addition, information is provided on the most novel approaches for the study of mastitis including the use of mutant pathogen strains and transgenic mice.

In this paper, we provide an analysis of the requantization problem in order to improve the requantization process. This analysis is based on theoretical R–D results of requantized Laplacian sources instead of minimizing requantization errors as commonly found in the literature. We derive the effective quantizer characteristic by applying superposition to the quantizer characteristics of encoder and transcoder. Further investigation shows that the effective quantizer has a periodic property. Using the memoryless property of the probability distribution function and the periodic property of the effective quantizer characteristic, we derive expressions for entropy and distortion. Based on the theoretical R–D model, requantization for fine and coarse quantized signals is investigated. The analysis of the R–D behavior shows that a heuristic can be derived which improves the requantization process. Finally, the results from the R–D analysis are verified for requantization transcoding of H.264/AVC video streams. We show that the transcoding process for H.264/AVC video streams, which corresponds to coarse quantization, is improved with gains up to 1dB.

This paper presents an efficient receiver-aware video transcoding system that systematically chooses the optimal transcoding operation from multiple options while meeting network and user constraints. Multi-objective optimization is used to select the best transcoding method that minimizes transcoding complexity and memory usage while ensuring the client constrainst of bitrate and requested quality are fulfilled.

Accessing multimedia services via fixed and wireless networks has become common practice. These services are typically much more sensitive to packet loss, delay and/or congestion than traditional services. In particular, multimedia data is often time critical and, as a result, network issues are not well tolerated and significantly deteriorate the user’s Quality of Experience (QoE). Therefore, the authors propose a QoE optimization platform that is able to mitigate problems that might occur at any location in the delivery path from service provider to customer. More specifically, the distributed architecture supports overlay routing to circumvent erratic parts of the network core. In addition, it comprises proxy components that realize last mile optimization through automatic bandwidth management and the application of processing on multimedia flows. This paper introduces a transcoding service for this proxy component which enables the transformation of H.264/AVC video flows to an arbitrary bitrate. Through representative experimental results, the authors illustrate how this addition enhances the QoE optimization capabilities of the proposed platform by allowing the proxy component to compute more flexible and effective bandwidth distributions.

In this paper, efficient solutions for requantization transcoding in H.264/AVC are presented. By requantizing residual coefficients in the bitstream, different error components can appear in the transcoded video stream. Firstly, a requantization error is present due to successive quantization in encoder and transcoder. In addition to the requantization error, the loss of information caused by coarser quantization will propagate due to dependencies in the bitstream. Because of the use of intra prediction and motion-compensated prediction in H.264/AVC, both spatial and temporal drift propagation arise in transcoded H.264/AVC video streams. The spatial drift in intra-predicted blocks results from mismatches in the surrounding prediction pixels as a consequence of requantization. In this paper, both spatial and temporal drift components are analyzed. As is shown, spatial drift has a determining impact on the visual quality of transcoded video streams in H.264/AVC. In particular, this type of drift results in serious distortion and disturbing artifacts in the transcoded video stream. In order to avoid the spatially propagating distortion, we introduce transcoding architectures based on spatial compensation techniques. By combining the individual temporal and spatial compensation approaches and applying different techniques based on the picture and/or macroblock type, overall architectures are obtained that provide a trade-off between computational complexity and rate-distortion performance. The complexity of the presented architectures is significantly reduced when compared to cascaded decoder–encoder solutions, which are typically used for H.264/AVC transcoding. The reduction in complexity is particularly large for the solution which uses spatial compensation only. When compared to traditional solutions without spatial compensation, both visual and objective quality results are highly improved.

In this paper, we examine spatial resolution downscaling transcoding for H.264/AVC video coding. A number of advanced coding tools limit the applicability of techniques, which were developed for previous video coding standards. We present a spatial resolution reduction transcoding architecture for H.264/AVC, which extends open-loop transcoding with a low-complexity compensation technique in the reduced-resolution domain. The proposed architecture tackles the problems in H.264/AVC and avoids visual artifacts in the transcoded sequence, while keeping complexity significantly lower than more traditional cascaded decoder–encoder architectures. The refinement step of the proposed architecture can be used to further improve rate-distortion performance, at the cost of additional complexity. In this way, a dynamic-complexity transcoder is rendered possible. We present a thorough investigation of the problems related to motion and residual data mapping, leading to a transcoding solution resulting in fully compliant reduced-size H.264/AVC bitstreams.

Requantization transcoding is a method for reducing the bit rate of compressed video bitstreams. Most research on requantization is concerned with the architectural design, the selection of a suitable quantizer, or the reduction of requantization errors. In this paper, we propose to incorporate a new dimension in requantization transcoding: the quantization offset. We compare two requantization methods: increasing the quantization step size and decreasing the quantization offset. Furthermore, we propose a novel heuristic for requantization transcoding based on a theoretical rate-distortion analysis. The experimental results for H.264/AVC video show that requantization is improved in rate-distortion sense with gains up to 1 dB for open-loop requantization of B pictures compared to requantization with fixed quantization offset.

In this paper, we investigate transrating architectures for H.264/AVC video streams. Basic architectures are presented with their strengths and weaknesses. None of the existing architectures provide an appropriate solution for H.264/AVC transrating with an optimal balance between visual quality and complexity. In order to find such an appropriate solution, we propose the use of mixed transrating architectures. These architectures combine different transrating techniques which are applied depending on the picture/macroblock type. The intra-predicted pictures are decoded and re-encoded, while open-loop transrating or transrating with compensation is applied to motion-compensated pictures. Performance results show that the mixed architecture which applies spatial compensation to motion-compensated pictures gives rate-distortion results which approach the cascade of decoder and re-encoder with a complexity only slightly higher than the open-loop transrater. Adding temporal compensation for motion-compensated pictures further improves the visual quality, albeit to a lower extent, at the expense of increased complexity.

In this paper, we present motion-refined transcoding of H.264/AVC streams to SVC in the transform domain. By accurately taking into account both rate and distortion in the different layers on the one hand, and the SVC inter-layer motion prediction mechanisms on the other hand, the proposed transcoding architecture is able to improve rate-distortion performance over existing approaches. We propose a multilayer control mechanism that trades off performance between the different layers, resulting in 0.5 dB gains in the output SVC base layer.

The scalable extension of H.264/AVC (SVC) was recently standardized, and offers scalability at a minor penalty in rate-distortion efficiency when compared to single-layer H.264/AVC coding. In SVC, a scaled version of the original video sequence can easily be extracted by dropping layers from the stream. However, most of the video content nowadays is still produced in a single-layer format. While decoding and reencoding is a possible solution to introduce scalability in the existing bitstreams, this is an approach which requires a tremendous amount of time and effort. In this paper, we show that transcoding can be used to intelligently derive scalable bitstreams from existing single-layer streams. We focus on SNR scalability, and introduce techniques that are able to create multiple quality layers in the bitstreams. We also discuss bitstream rewriting from SVC to H.264/AVC, and examine how our newly proposed architectures can benefit from the changes that were introduced for bitstream rewriting. Architectures with different rate distribution flexibility and computational complexity are discussed. Rate-distortion performance of transcoding is shown to be comparable to that of reencoding at a fraction of the time needed for the latter.

In this paper we present a number of advanced concepts with respect to the transformation of residual blocks in video coders, which go beyond what is incorporated in today's video coding standards. Some of these concepts will undoubtedly be adopted as part of future standards. We discuss directional transforms for extrapolation-based prediction schemes, shape-adaptive transformation for object-based coding, and large transform sizes. For the latter we provide in-depth coding efficiency results which clearly illustrate the potential benefit, especially for high definition source material, which will dominate the requirements of tomorrow's video coding standards. The compression efficiency gains that can be achieved with large block transforms range from 6 to 25%. Finally we also comment on the paradigm of coupling partition and transform areas, a principle which can be applied to block transforms as well as to shape-adaptive transforms for object-based coding.

When combining non-rectangular (shape-adaptive) partitioning of inter pictures with a rectangular block transform, some of the transforms will be applied to a residual signal which originates from two different predictions. This is a condition that is never encountered in any of the existing video coding standards, and the impact of this on the performance of the transform coder has not been investigated. In this paper we investigate the effect of these mixed-signal blocks on the coding gain for various transforms, and we compare these against the optimal KLT gain. We find that, despite the transformed residual block being composed of two parts that were predicted from different areas of the reference picture, correlation within mixed blocks is very similar to that of normal blocks. The DCT is only marginally suboptimal w.r.t. KLT. KLT has practical issues that will reduce its coding gain or increase the signaling overhead: transform bases need to be quantized and transmitted, or a number of fixed bases needs to be chosen offline. Therefore we recommend DCT be used for all types of blocks.

More and more, multimedia services are being accessed via fixed and mobile networks. These services are typically much more sensitive to packet loss, delay and/or congestion than traditional services. In particular, multimedia data is often time critical and, as a result, network issues are not well tolerated and significantly deteriorate the userpsilas quality of experience (QoE). We therefore propose a QoE optimization platform that is able to mitigate problems that might occur at any location in the delivery path from service provider to customer. More specifically, the distributed architecture supports overlay routing to circumvent erratic parts of the network core. In addition, it comprises proxy components that realize last mile optimization through automatic bandwidth management and the application of processing on multimedia flows. In this paper we introduce a transcoding service for this proxy component which enables the transformation of H.264/AVC video flows to an arbitrary bit rate. Through representative experimental results, we illustrate how this addition enhances the QoE optimization capabilities of the proposed platform by allowing the proxy component to compute more flexible and effective bandwidth distributions.

In previous work, we introduced an H.264/AVC-to-SVC transcoder for creating SVC streams with multiple quality layers from a single-layer H.264/AVC stream. This architecture was able to restrain the error drift due to requantization of the residual coefficients. In this paper, we show that it is possible to further reduce the complexity, and completely eliminate the drift in the enhancement layer, by making use of the bitstream rewriting functionality in SVC. We propose different novel architectures, which are able to flexibly distribute the data among the different created layers.

To attain efficient coding of sequences with complex motion activity, modern video coding standards allow variable block sizes to be employed in temporal prediction. A block with complex motion can be partitioned into two equal-sized halves or into four quadrants. In this paper we study the impact of allowing blocks to be partitioned in two unequal subpartitions. Additionally, we allow block partitioning along diagonal edges. These provisions allows encoders to better adapt to the local characteristics of the motion activity in a video sequence. We verified experimentally that the presence of partitioning edges that do not coincide with transform boundaries does not negatively impact the decorrelating strength of the residual transform, so the proposed extended partitioning strategies can be applied regardless of the details of the residual coder. Implementing the proposed extended partitioning modes in an H.264/AVC coder at the macroblock and submacroblock level, we observe that coding efficiency gains are greatest in low-resolution sequences, where moving features in the video sequence tend to be more spatially localized. For CIF and QCIF sequences we achieve a bit rate reduction of about 3-6% over a wide fidelity range.

In this paper, dynamic rate shaping for H.264/AVC intra-coded video streams is investigated. An analysis of the distortion distinguishes different error components that lead to the degradation of the output video stream. Experimental results show that the propagation error due to intra prediction has a major impact on the visual quality. This results from the highly increased number of dependencies which are invoked by the H.264/AVC intra prediction. In order to eliminate the propagation error, we propose to use single-loop compensation techniques. Both objective and subjective results show that the compensation techniques highly improve the visual quality.