Advanced solutions for quality-oriented multimedia broadcasting

Multimedia content is increasingly being delivered via different types of networks to viewers in a variety of locations and contexts using a variety of devices. The ubiquitous nature of multimedia services comes at a cost, however. The successful delivery of multimedia services will require overcoming numerous technological challenges many of which have a direct effect on the quality of the multimedia experience. For example, due to dynamically changing requirements and networking conditions, the delivery of multimedia content has traditionally adopted a best effort approach. However, this approach has often led to the end-user perceived quality of multimedia-based services being negatively affected. Yet the quality of multimedia content is a vital issue for the continued acceptance and proliferation of these services. Indeed, end-users are becoming increasingly quality-aware in their expectations of multimedia experience and demand an ever-widening spectrum of rich multimedia-based services. As a consequence, there is a continuous and extensive research effort, by both industry and academia, to find solutions for improving the quality of multimedia content delivered to the users; as well, international standards bodies, such as the International Telecommunication Union (ITU), are renewing their effort on the standardization of multimedia technologies. There are very different directions in which research has attempted to find solutions in order to improve the quality of the rich media content delivered over various network types. It is in this context that this special issue on broadcast multimedia quality of the IEEE Transactions on Broadcasting illustrates some of these avenues and presents some of the most significant research results obtained by various teams of researchers from many countries. This special issue provides an example, albeit inevitably limited, of the richness and breath of the current research on multimedia broadcasting services. The research i- - ssues addressed in this special issue include, among others, factors that influence user perceived quality, encoding-related quality assessment and control, transmission and coverage-based solutions and objective quality measurements

Error concealment-aware encoding for robust video transmission

In this paper an error concealment-aware encoding scheme is proposed to improve the quality of decoded video in broadcast environments prone to transmission errors and data loss. The proposed scheme is based on a scalable coding approach where the best error concealment (EC) methods to be used at the decoder are optimally determined at the encoder and signalled to the decoder through SEI messages. Such optimal EC modes are found by simulating transmission losses followed by a lagrangian optimisation of the signalling rate - EC distortion cost. A generalised saliency-weighted distortion is used and the residue between coded frames and their EC substitutes is encoded using a rate-controlled enhancement layer. When data loss occurs the decoder uses the signalling information is used at the decoder, in case of data loss, to improve the reconstruction quality. The simulation results show that the proposed method achieves consistent quality gains in comparison with other reference methods and previous works. Using only the EC mode signalling, i.e., without any residue transmitted in the enhancement layer, an average PSNR gain up to 2.95 dB is achieved, while using the full EC-aware scheme, i.e., including residue encoded in the enhancement layer, the proposed scheme outperforms other comparable methods, with PSNR gain up to 3.79 dB

Error resilience and concealment techniques for high-efficiency video coding

This thesis investigates the problem of robust coding and error concealment in High Efficiency Video Coding (HEVC). After a review of the current state of the art, a simulation study about error robustness, revealed that the HEVC has weak protection against network losses with significant impact on video quality degradation. Based on this evidence, the first contribution of this work is a new method to reduce the temporal dependencies between motion vectors, by improving the decoded video quality without compromising the compression efficiency. The second contribution of this thesis is a two-stage approach for reducing the mismatch of temporal predictions in case of video streams received with errors or lost data. At the encoding stage, the reference pictures are dynamically distributed based on a constrained Lagrangian rate-distortion optimization to reduce the number of predictions from a single reference. At the streaming stage, a prioritization algorithm, based on spatial dependencies, selects a reduced set of motion vectors to be transmitted, as side information, to reduce mismatched motion predictions at the decoder. The problem of error concealment-aware video coding is also investigated to enhance the overall error robustness. A new approach based on scalable coding and optimally error concealment selection is proposed, where the optimal error concealment modes are found by simulating transmission losses, followed by a saliency-weighted optimisation. Moreover, recovery residual information is encoded using a rate-controlled enhancement layer. Both are transmitted to the decoder to be used in case of data loss. Finally, an adaptive error resilience scheme is proposed to dynamically predict the video stream that achieves the highest decoded quality for a particular loss case. A neural network selects among the various video streams, encoded with different levels of compression efficiency and error protection, based on information from the video signal, the coded stream and the transmission network. Overall, the new robust video coding methods investigated in this thesis yield consistent quality gains in comparison with other existing methods and also the ones implemented in the HEVC reference software. Furthermore, the trade-off between coding efficiency and error robustness is also better in the proposed methods

Towards video streaming in IoT environments: vehicular communication perspective

Multimedia oriented Internet of Things (IoT) enables pervasive and real-time communication of video, audio and image data among devices in an immediate surroundings. Today's vehicles have the capability of supporting real time multimedia acquisition. Vehicles with high illuminating infrared cameras and customized sensors can communicate with other on-road devices using dedicated short-range communication (DSRC) and 5G enabled communication technologies. Real time incidence of both urban and highway vehicular traffic environment can be captured and transmitted using vehicle-to-vehicle and vehicle-to-infrastructure communication modes. Video streaming in vehicular IoT (VSV-IoT) environments is in growing stage with several challenges that need to be addressed ranging from limited resources in IoT devices, intermittent connection in vehicular networks, heterogeneous devices, dynamism and scalability in video encoding, bandwidth underutilization in video delivery, and attaining application-precise quality of service in video streaming. In this context, this paper presents a comprehensive review on video streaming in IoT environments focusing on vehicular communication perspective. Specifically, significance of video streaming in vehicular IoT environments is highlighted focusing on integration of vehicular communication with 5G enabled IoT technologies, and smart city oriented application areas for VSV-IoT. A taxonomy is presented for the classification of related literature on video streaming in vehicular network environments. Following the taxonomy, critical review of literature is performed focusing on major functional model, strengths and weaknesses. Metrics for video streaming in vehicular IoT environments are derived and comparatively analyzed in terms of their usage and evaluation capabilities. Open research challenges in VSV-IoT are identified as future directions of research in the area. The survey would benefit both IoT and vehicle industry practitioners and researchers, in terms of augmenting understanding of vehicular video streaming and its IoT related trends and issues

A maximum likelihood approach to video error correction applied to H.264 decoding

Video error concealment has long been identified as the last line of defense against transmission errors. This is especially true for real time video communication systems where retransmissions are rarely used because of timing constraints. Since error handling is outside the scope of video coding standards, decoders may choose to simply ignore the corrupted packets, or attempt to decode their content. Video error correction is a viable alternative to deal with transmission errors when corrupted packets reach their destination. Until now, these approaches have received little considerations. This is mainly because the proposed methods either rely on specific coding tools or constraints, or require far too many computations compared to video error concealment techniques. In this thesis, we propose a novel video error correction method based on maximum likelihood decoding. The method estimates the likeliest syntactically valid video slice content based on the erroneous video packets rather than discarding the content, and concealing the missing information. Such content is obtained by combining the likelihood of the candidate codewords with the bit modification likelihood associated to each candidate. We propose two solutions centered around our maximum likelihood decoding approach. First, we introduce a slice-level video error correction method. Furthermore, we show how to integrate the soft-output information shared by the channel decoder to evaluate the bit modification likelihood. We also show that it is possible to use our maximum likelihood decoding approach when soft-output information is not available. Then, we refine the solution at the syntax-element-level. The final solution we obtain can be used in real-time communication systems as it is computationally inexpensive compared to the slice-level solution, or the solutions proposed in the literature. Our final solution is then applied to the correction of videos conforming to the H.264 Baseline profile. We selected three 720x480 sequences, five 704x576 sequences, and one 720x576 sequence to run simulations. Each sequence was coded at a target bitrate of 1 Mbps, 1.2 Mbps, and 1.5 Mbps. All 27 sequences were then submitted to a noisy channel with a bit error rate ranging from 10−5 to 10−3. Our 5400 observations show a PSNR improvement of 1.69 dB over the video error concealment method implemented in the H.264 reference software. Furthermore, our results also indicate a 0.42 dB PSNR improvement over state-of-the-art error concealment STBMA+PDE

The application of z-numbers in fuzzy decision making: The state of the art

A Z-number is very powerful in describing imperfect information, in which fuzzy numbers are paired such that the partially reliable information is properly processed. During a decision-making process, human beings always use natural language to describe their preferences, and the decision information is usually imprecise and partially reliable. The nature of the Z-number, which is composed of the restriction and reliability components, has made it a powerful tool for depicting certain decision information. Its strengths and advantages have attracted many researchers worldwide to further study and extend its theory and applications. The current research trend on Z-numbers has shown an increasing interest among researchers in the fuzzy set theory, especially its application to decision making. This paper reviews the application of Z-numbers in decision making, in which previous decision-making models based on Z-numbers are analyzed to identify their strengths and contributions. The decision making based on Z-numbers improves the reliability of the decision information and makes it more meaningful. Another scope that is closely related to decision making, namely, the ranking of Z-numbers, is also reviewed. Then, the evaluative analysis of the Z-numbers is conducted to evaluate the performance of Z-numbers in decision making. Future directions and recommendations on the applications of Z-numbers in decision making are provided at the end of this review

Unravelling the interplay between microbiome, inflammation, metabolic dysregulation and endometrial carcinogenesis

Background Inflammatory and metabolic cues have long been associated with the pathogenesis of endometrial cancer. Increasing evidence implicates the reproductive tract microbiota with health and disease states, however its role in metabolic and inflammatory dysregulation in the context of endometrial oncogenesis is poorly described. Aims The overarching goal of this thesis was to explore diabetes and microbial dysbiosis as complicit factors in endometrial cancer. The first aim was to critically appraise the strength of epidemiological evidence for associations between diabetes and anti-diabetic interventions and the risk of endometrial cancer and other gynaecological or obstetric outcomes. The second aim was to investigate if genuine microbial signals from low bacterial biomass sites of the upper genital tract can be detected above background and if so, determine if they exist as a microbial continuum along the length of female genital tract and rectum of endometrial cancer patients and patients with benign intra- or extrauterine pathology. The third aim was to test the hypothesis that endometrial cancer patients harbour a distinctive microbial fingerprint in their genital tract and rectum compared to benign controls that contributes to endometrial cell proliferation and inflammation in a 3-dimensional endometrial organoid model. Lastly, this thesis aimed to validate benign and malignant endometrial organoids as tools for disease modelling by interrogating their phenotypic, genetic and epigenetic resemblance to parent tissue. Results An umbrella review of existing meta-analyses demonstrated suggestive evidence supporting a positive association between diabetes and endometrial cancer and improved survival in metformin users. Increased endometrial cancer mortality among diabetic patients was only supported by weak evidence. Metataxonomics-based characterisation of microbiota and qPCR showed that a subset of benign and endometrial cancer patients harbour microbial communities distinguishable from background contaminants. A microbial continuum along the genital tract is most evident in benign patients compared to endometrial cancer patients, whereas vaginal microbiota is poorly correlated with rectal microbiota in both cohorts. Endometrial cancer is associated with reduced cervicovaginal and rectal bacterial load and compositionally characterised by Lactobacillus depletion, increased microbial diversity and enrichment of Porphyromonas, Prevotella, Peptoniphilus and Anaerococcus in the lower genital tract and endometrium. Microbiome-host interactions were studied using 3D endometrial organoid models, which were shown to be morphologically and (epi)genetically consistent with progenitor tissue. L. crispatus supernatant decreases endometrial cancer organoid viability at high concentrations and does not significantly affect inflammatory pathways in benign or endometrial cancer organoids as measured by cytokine secretion. Discussion & Conclusion Metabolic dysregulation and microbiota alterations are associated with endometrial cancer. L. crispatus, a female genital tract commensal, does not interfere with inflammatory signalling in endometrial organoids. Further demystifying which host pathways altered microbiota might influence could provide insights in the context of microbiota manipulation for clinical purposes.Open Acces