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Consumption and production of video signals drastically changed in recent years. Due to the advances in digital consumer technology and the growing availability of fast and reliable internet connections, an increasing amount of digital video sequences are being produced, stored and shared every day in different parts of the world. Video signals are inherently larger in size than other types of multimedia signals. For this reason in order to allow transmission and storage of such data, more efficient compression technology is needed. In this thesis novel methods for enhancing the efficiency of current and next generation video codecs are investigated. Several aspects of interest to video coding technology are taken into account, from computational complexity and compliance to standardisation efforts, to compression efficiency and quality of the decoded signals. Compression can be achieved exploiting redundancies by computing a prediction of a part of the signal using previously encoded portions of the signal. Novel prediction methods are proposed in this thesis based on analytical or statistical models with the aim of providing a solid theoretical basis to support the algorithmic implementation. It is shown in the thesis that appropriately defined synthetic content can be introduced in the signal to compensate for the lack of certain characteristics in the original content. Some of the methods proposed in this thesis aim to target a broader set of use cases than those typically addressed by conventional video coding methods, such as ultra high definition content or coding under high quality conditions.

Advances in digital camera technology have led to the development of image sensors that are capable of capturing High Dynamic Range (HDR) images. Although this has enabled the capture of greater depths of colour and illumination, there remain problems with regards to transmitting and displaying the HDR image data. Current consumer level displays are designed to only show images with a depth of 8-bits per pixel per channel. Typical HDR images can be 10-bits per pixel per channel and upwards, leading to the first problem, how to display HDR images on Standard Dynamic Range (SDR) displays. This is linked to a further problem, that of transmitting the HDR data to the SDR devices, due to the fact that most state-of-the-art image and video coding standards deal with only SDR data. Further, as with most technologies of this kind, current HDR displays are extremely expensive. Furthermore, media broadcast organisations have invested significant sums of money into their current architecture and are unwilling to completely change their systems at further cost.

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Multiple Description Coding (MDC) was fi rst formulated by A. Gersho and H. Witsenhausen as a way to improve the robustness of telephony links to outages. Lots of studies have been done in this area up to now. Another application of MDC is the transmission of an image in diff erent descriptions. If because of the link outage during transmission, any one of the descriptions fails, the image could still be reconstructed with some quality at the decoder side. In video coding, inter prediction is a way to reduce temporal redundancy. From an information theoretical point of view, one can model inter prediction with Causal Video Coding (CVC). If because of link outage, we lose any I-frame, how can we reconstruct the corresponding P- or B-frames at the decoder? In this thesis, we are interested in answering this question and we call this scenario as causal video coding with possible loss of the fi rst encoded frame and we denote it by CVC-PL as PL stands for possible loss. In this thesis for the fi rst time, CVC-PL is investigated. Although, due to lack of time, we mostly study two-frame CVC-PL, we extend the problem to M-frame CVC-PL as well. To provide more insight into two-frame CVC-PL, we derive an outer-bound to the achievable rate-distortion sets to show that CVC-PL is a subset of the region combining CVC and peer-to-peer coding. In addition, we propose and prove a new achievable region to highlight the fact that two-frame CVC-PL could be viewed as MDC followed by CVC. Afterwards, we present the main theorem of this thesis, which is the minimum total rate of CVC-PL with two jointly Gaussian distributed sources, i.e. X1 and X2 with normalized correlation coeffi cient r, for di fferent distortion pro files (D1,D2,D3). Defi ning Dr = r^2(D1 -1) + 1, we show that for small D3, i.e. D3 < Dr +D2 -1, CVC-PL could be treated as CVC with two jointly Gaussian distributed sources; for large D3, i.e. D3 > DrD2/(Dr+D2-DrD2), CVC-PL could be treated as two parallel peer-to-peer networks with distortion constraints D1 and D2; and for the other cases of D3, the minimum total rate is 0.5 log (1+ ??)(D3+??)/ (Dr+?? )(D2+?? ) + 0.5 log Dr/(D1D3) where ??=D3-DrD2+r[(1-D1)(1-D2)(D3-Dr)(D3-D2)]^0.5/[Dr+D2-(D3+1) ] We also determine the optimal coding scheme which achieves the minimum total rate. We conclude the thesis by comparing the scenario of CVC-PL with two frames with a coding scheme, in which both of the sources are available at the encoders, i.e. distributed source coding versus centralized source coding. We show that for small D2 or large D3, the distributed source coding can perform as good as the centralized source coding. Finally, we talk about future work and extend and formulate the problem for M sources.

The primary objective of this thesis is to provide a low-complexity rate-distortion optimal coding mode selection method in digital video encoding. To achieve optimal compression efficiency in the rate-distortion framework with low computational complexity, we first propose a rate-distortion model and then apply it to the coding mode selection problem. The computational complexity of the proposed method is very low compared to overall encoder complexity because the proposed method uses simple image properties such as variance that can be obtained easily. Also, the proposed method gives significant PSNR gains over the mode selection scheme used in TM5 for MPEG-2 because the rate-distortion model considers rate constraints of each mode as well as distortion. We extend the model-based mode selection approach to motion vector selection for further improvement of the coding efficiency. In addition to our theoretical work, we present practical solutions to real-time implementation of encoder modules including our proposed mode selection method on digital signal processors. First, we investigate the features provided by most of the recent digital signal processors, for example, hierarchical memory structure and efficient data transfer between on-chip and off-chip memory, and then present practical approaches for real-time implementation of a video encoder system with efficient use of the features.

Dans cette étude, nous utilisons des caractéristiques locales/globales en vue d’améliorer la chaîne de transmission des séquences de vidéos. Ce travail est divisé en quatre parties principales qui mettent à profit les caractéristiques de contenu vidéo. La première partie introduit un modèle de prédiction de paramètres d’un encodeur basé sur la complexité du contenu. Ce modèle utilise le débit, la distorsion, ainsi que la complexité de différentes configurations de paramètres afin d’obtenir des valeurs souhaitables (recommandées) de paramètres d’encodage. Nous identifions ensuite le lien en les caractéristiques du contenu et ces valeurs recommandées afin de construire le modèle de prédiction. La deuxième partie illustre le schéma de l’encodage à description multiple (Multiple Description Coding ou MDC, en anglais) que nous proposons dans ces travaux. Celui-ci est optimisé pour des MDC d’ordre-hauts. Le décodage correspondant et la procédure de récupération de l’erreur contenu-dépendant sont également étudiés et identifiés. La qualité de la vidéo reçue a été évaluée subjectivement. En analysant les résultats des expériences subjectives, nous introduisons alors un schéma adaptatif, c’est-à-dire adapté à la connaissance du contenu vidéo. Enfin, nous avons simulé un scénario d’application afin d’évaluer un taux de débit réaliste. Dans la troisième partie, nous utilisons une carte de déplacement, calculées au travers des propriétés de mouvement du contenu vidéo, comme entrée pour l’algorithme de masquage d’erreur par recouvrement (inpainting based error concealment algorithm). Une expérience subjective a été conduite afin d’évaluer l’algorithme et d’étudier la perturbation de l’observateur au visionnage de la vidéo traitée. La quatrième partie possèdent deux sous-parties. La première se penche sur les algorithmes de sélections par HRC pour les grandes bases de données de vidéos. La deuxième partie introduit l’évaluation de la qualité vidéo utilisant la connaissance du contenu global non-référencé. / In this work, the global/local content characteristics are utilized in order to improve the delivery chain of the video sequences. The work is divided into four main parts that take advantages of video content features. The first part introduces a joint content-complexity encoder parameters prediction model. This model uses bitrate, distortion, and complexity of different parameters configurations in order to get the recommended encoder parameters value. Then, the links between content features and the recommended values are identified. Finally, the prediction model is built using these features and the recommended encoder parameter values. The second part illustrates the proposed multiple description coding (MDC) scheme that is optimized for high-order MDC. The corresponding decoding and content-dependent error recovery procedures are also identified. The quality of the received videos is evaluated subjectively. By analyzing the subjective experiment results, an adaptive, i.e. content-aware, scheme is introduced. Finally, an application scenario is simulated to study the realistic bitrate consumption. The third part uses the motion properties of a content to introduce a motion map that will be used as an input for the modified state-of-the-art inpainting based error concealment algorithm. A subjective experiment was conducted to evaluate the algorithm and also to study the content-aware observer’s disturbance when perceiving the processed videos. The fourth part has two sub-parts, the first one is about HRC selection algorithms for the large-scale video database with an improved performance evaluation measures for video quality assessment algorithms using training and validation sets. The second part introduces global content aware no-reference video quality assessment.

3D video is a technology that has seen a tremendous attention in the recent years. Multiview Video Coding (MVC) is an extension of the popular H.264 video coding standard and is commonly used to compress 3D videos. It offers an improvement of 20% to 50% in compression efficiency over simulcast encoding of multiview videos using the conventional H.264 video coding standard. However, there are two important problems associated with it: (i) its superior compression performance comes at the cost of significantly higher computational complexity which hampers the real-world realization of MVC encoder in applications such as 3D live broadcasting and interactive Free Viewpoint Television (FTV), and (ii) compressed 3D videos can suffer from packet loss during transmission, which can degrade the viewing quality of the 3D video at the decoder. This thesis aims to solve these problems by presenting techniques to reduce the computational complexity of the MVC encoder and by proposing a consistent error concealment technique for frame losses in 3D video transmission. The thesis first analyses the complexity of the MVC encoder. It then proposes two novel techniques to reduce the complexity of motion and disparity estimation. The first method achieves complexity reduction in the disparity estimation process by exploiting the relationship between temporal levels, type of macroblocks and search ranges while the second method achieves it by exploiting the geometrical relation- ship between motion and disparity vectors in stereo frames. These two methods are then combined with other state-of-the-art methods in a unique framework where gains add up. Experimental results show that the proposed low-complexity framework can reduce the encoding time of the standard MVC encoder by over 93% while maintaining similar compression efficiency performance. The addition of new View Synthesis Prediction (VSP) modes to the MVC encoding framework improves the compression efficiency of MVC. However, testing additional modes comes at the cost of increased encoding complexity. In order to reduce the encoding complexity, the thesis, next, proposes a bayesian early mode decision technique for a VSP enhanced MVC coder. It exploits the statistical similarities between the RD costs of the VSP SKIP mode in neighbouring views to terminate the mode decision process early. Results indicate that the proposed technique can reduce the encoding time of the enhanced MVC coder by over 33% at similar compression efficiency levels. Finally, compressed 3D videos are usually required to be broadcast to a large number of users where transmission errors can lead to frame losses which can degrade the video quality at the decoder. A simple reconstruction of the lost frames can lead to inconsistent reconstruction of the 3D scene which may negatively affect the viewing experience of a user. In order to solve this problem, the thesis proposes, at the end, a consistency model for recovering frames lost during transmission. The proposed consistency model is used to evaluate inter-view and temporal consistencies while selecting candidate blocks for concealment. Experimental results show that the proposed technique is able to recover the lost frames with high consistency and better quality than two standard error concealment methods and a baseline technique based on the boundary matching algorithm.