Ces dernières années, les contenus vidéos ont évolué très rapidement. En effet, les télévisions (TV) ont rapidement évolué vers l’Ultra Haute résolution (UHD), la Haute Fréquence d’images (HFR) ou la stéréoscopie (3D). La tendance actuelle est à l’imagerie à Haute Dynamique de luminance (HDR). Ces technologies permettent de reproduire des images beaucoup plus lumineuses que celles des écrans actuels. Chacune de ces améliorations représente une augmentation du coût de stockage et nécessite la création de nouveaux standards de compression vidéo, toujours plus performant. La majorité des consommateurs est actuellement équipé de TV ayant une Dynamique Standard (SDR) qui ne supportent pas les contenus HDR et ils vont lentement renouveler leurs écrans pour un HDR. Il est donc important de délivrer un signal HDR qui puisse être décodé par ces deux types d’écrans. Cette rétro compatibilité est rendue possible par un outil appelé TMO (Tone Mapping Operator) qui transforme un contenu HDR en une version SDR. Au travers de cette thèse, nous explorons de nouvelles méthodes pour améliorer la compression HDR rétro compatible. Premièrement, nous concevons un TMO qui optimise les performances d’un schéma de compression scalable où une couche de base et d’amélioration sont envoyées pour reconstruire les contenus HDR et SDR. Il est démontré que le TMO optimal dépend seulement de la couche SDR de base et que le problème de minimisation peut être séparé en deux étapes consécutives. Pour ces raisons, nous proposons ensuite un autre TMO conçu pour optimiser les performances d’un schéma de compression utilisant uniquement une couche de base mais avec un modèle amélioré et plus précis. Ces deux travaux optimisent des TMO pour images fixes. Par la suite, la thèse se concentre sur l’optimisation de TMO spécifiques à la vidéo. Cependant, on y démontre que l’utilisation d’une prédiction pondérée pour la compression SDR est aussi bon voir meilleur que d’utiliser un TMO optimisé temporellement. Pour ces raisons, un nouvel algorithme et de nouveaux modes de prédictions pondérées sont proposés pour gérer plus efficacement la large diversité des changements lumineux dans les séquences vidéos. / In recent years, video content evolved very quickly. Indeed, televisions (TV) quickly evolved to Ultra High Definition (UHD), High Frame Rate (HFR) or stereoscopy (3D). The recent trend is towards High Dynamic range (HDR). These new technologies allow the reproduction of much brighter images than for actual displays. Each of these improvements represents an increase in storage cost and therefore requires the creation of new video compression standards, always more efficient. The majority of consumers are currently equipped with Standard Dynamic Range (SDR) displays, that cannot handle HDR content. Consumers will slowly renew their display to an HDR one and it is therefore of great importance to deliver an HDR signal that can be decoded by both SDR and HDR displays. Such backward compatibility is provided by a tool called Tone Mapping Operator (TMO) which transforms an HDR content into an SDR version. In this thesis, we explore new methods to improve the backward compatible HDR compression. First, we design a Tone Mapping to optimize scalable compression scheme performances where a base and an enhancement layer are sent to reconstruct the SDR and HDR content. It is demonstrated that the optimum TMO only depends on the SDR base layer and that the minimization problem can be separated in two consecutive minimization steps. Based on these observations, we then propose another TMO designed to optimize the performances of compression schemes using only a base layer but with an enhanced and more precise model. Both of these works optimize TMO for still images. Thereafter, this thesis focuses on the optimization of video-specific TMO. However, we demonstrate that using a weighted prediction for the SDR compression is as good or even better than using a temporally optimized TMO. Therefore, we proposed a new weighted prediction algorithm and new weighted prediction modes to handle more efficiently the large diversity of brightness variations in video sequences.

<p>This thesis explores the possibilities of avoiding the issues generally associated with compression of noisy imagery, through the usage of vector quantization. By utilizing the learning aspects of vector quantization, image processing operations such as noise reduction could be implemented in a straightforward way. Several techniques are presented and evaluated. A direct comparison shows that for noisy imagery, vector quantization, in spite of it's simplicity, has clear advantages over MPEG-4 encoding.</p>

This thesis explores the possibilities of avoiding the issues generally associated with compression of noisy imagery, through the usage of vector quantization. By utilizing the learning aspects of vector quantization, image processing operations such as noise reduction could be implemented in a straightforward way. Several techniques are presented and evaluated. A direct comparison shows that for noisy imagery, vector quantization, in spite of it's simplicity, has clear advantages over MPEG-4 encoding.

Algorithm-Based Efficient Approaches for Motion Estimation Systems Teahyung Lee 121 pages Directed by Dr. David V. Anderson This research addresses algorithms for efficient motion estimation systems. With the growth of wireless video system market, such as mobile imaging, digital still and video cameras, and video sensor network, low-power consumption is increasingly desirable for embedded video systems. Motion estimation typically needs considerable computations and is the basic block for many video applications. To implement low-power video systems using embedded devices and sensors, a CMOS imager has been developed that allows low-power computations on the focal plane. In this dissertation efficient motion estimation algorithms are presented to complement this platform. In the first part of dissertation we propose two algorithms regarding gradient-based optical flow estimation (OFE) to reduce computational complexity with high performance. The first is a checkerboard-type filtering (CBTF) algorithm for prefiltering and spatiotemporal derivative calculations. Another one is spatially recursive OFE frameworks using recursive LS (RLS) and/or matrix refinement to reduce the computational complexity for solving linear system of derivative values of image intensity in least-squares (LS)-OFE. From simulation results, CBTF and spatially recursive OFE show improved computational efficiency compared to conventional approaches with higher or similar performance. In the second part of dissertation we propose a new algorithm for video coding application to improve motion estimation and compensation performance in the wavelet domain. This new algorithm is for wavelet-based multi-resolution motion estimation (MRME) using temporal aliasing detection (TAD) to enhance rate-distortion (RD) performance under temporal aliasing noise. This technique gives competitive or better performance in terms of RD compared to conventional MRME and MRME with motion vector prediction through median filtering.

Video is the most demanding modality from the viewpoints of bandwidth, computational complexity, and resolution. Thus, there has been limited progress in the field of mobile video technology. In the research, the focus is on elastic wireless video technology, and its adaptation to diagnostic application requirements in real-time clinical assessment. It is important and timely to apply wireless video technology to real-time remote diagnosis of emergent medical events. This premise comes from initial successes in telehealth based on wired networks. The enablement of mobility (for the physician and/or the patient) by wireless communication will be a next major step, but this advance will depend on definitive and compelling demonstrations of reliability. Thus, an important goal of the research is to develop a complete methodology that will be embraced by physicians. Acute pediatric asthma has been identified as a domain where this new capability will be highly welcome. The research uses flexible and interactive algorithms for Region-of-Interest (ROI) processing. ROI processing is a useful approach to achieve the optimal balance in the quality-bandwidth tradeoff characteristic of visual communication services. The notion of ROI has been traditionally used mostly for foreground-background separation in scene rendering and manipulation, and only more recently for variably quality compression. Even when the latter goal is considered, quality criteria have been ad-hoc and at best useful for video conferencing, given that the medical domain has its own fidelity criteria. The research thus focuses on the design of an elastic ROI-based compression paradigm with medical diagnosis as a central criterion. The research describes the methodology to achieve elasticity through rate control algorithms at the encoder. An elastic non-parametric approach is proposed that uses a priori user-specified video quality information, quantifies this information, and incorporates this into the encoder in the form of region-quality mappings. This method is compared to a parametric bit allocation approach that is based on region-features and a set of tuning weights. A number of videos of actual patients were filmed and used as the video database for the developed algorithms. In testing the elastic non-parametric and parametric algorithms, both objective measures in the form of Peak Signal to Noise Ratio (PSNR), and subjective evaluations were used. Thus, in this work, the focus is on domain relevance of the algorithms developed, as opposed to network related issues such as packet losses. This is justified in that these may have broader value with other applications, and continuation of this work will include realistic network conditions. To summarize, the research shows the usefulness of ROI processing as a means of achieving a gain (in a bits per pixel sense) over uniform compression at the same bitrate. It also shows how quantifying a notion of functionally lossless video quality diagnostically lossless video quality in a video-based telehealth system, in a bits per pixel sense is useful from an applications and bitrate perspective. Finally, a combination of these two concepts is advantageous i.e. diagnostically lossless ROI video quality is achievable over bitrate limited channels.

Video compression is a key technology used in several multimedia applications. Improvements in the compression techniques together with the increasing speed and optimized architecture of the new family processors enable us to use this technology more in real time systems. H.264 (also known as MPEG-4 Part 10 or AVC - Advanced Video Coding), is the latest video coding standard which is noted for achieving very high data compression. While H.264 is superior to its predecessors, it has a very high computational complexity which makes its costly for real time applications. Thus, in order to perform video encoding with satisfactory speed there is an obvious need for reducing the computational complexity. New algorithms were developed for this purpose. The developed algorithms were implemented on Texas Instrument TMS320C64x family to be able to fulfill the requirement in optimized signal processing hardware with low power consumption which arises from the computational complexity and the need for portable devices in video processing technology. With the new algorithms developed, a computation reduction of 55% was achieved without loosing perceptual image quality. Furthermore, the algorithms were implemented on a DSP along with the networking functionality to obtain a video streaming system. The final system may be used in a wide range of fields from surveillance systems to mobile systems.

Multiview video is one of the emerging research areas especially among the video coding community. Transmission of multiview video over an error prone network is possible with efficient compression of these videos. But along with the studies for efficiently compressing the multiview video, new error concealment and error protection methods are also necessary to overcome the problems due to erroneous channel conditions in practical applications. In packet switching networks, packet losses may lead to block losses in a frame or the loss of an entire frame in an encoded video sequence. In recent years several algorithms are proposed to handle the loss of an entire frame efficiently. However methods for full frame losses in stereoscopic or multiview videos are limited in the literature. In this thesis a stereoscopic approach for full frame loss concealment of multiview video is proposed. In the proposed methods, the redundancy and disparity between the views and motion information between the previously decoded frames are used to estimate the lost frame. Even though multiview video can be composed of more than two views, at most three view are utilized for concealment. The performance of the proposed algorithms are tested against monoscopic methods and the conditions under which the proposed methods are superior are investigated. The proposed algorithms are applied to both stereoscopic and multiview video.

In this thesis, a number of novel techniques for error resilient coding and streaming for multiview video are presented. First of all, a novel coding technique for stereoscopic video is proposed where additional coding gain is achieved by downsampling one of the views spatially or temporally based on the well-known theory that the human visual system can perceive high frequencies in 3D from the higher quality view. Stereoscopic videos can be coded at a rate upto 1.2 times that of monoscopic videos with little visual quality degradation with the proposed coding technique. Next, a systematic method for design and optimization of multi-threaded multi-view video encoding/decoding algorithms using multi-core processors is proposed. The proposed multi-core decoding architectures are compliant with the current international standards, and enable multi-threaded processing with negligible loss of encoding efficiency and minimum processing overhead. End-to-end 3D Streaming system over Internet using current standards is implemented. A heuristic methodology for modeling the end-toend rate-distortion characteristic of this system is suggested and the parameters of the system is optimally selected using this model. End-to-end 3D Broadcasting system over DVB-H using current standards is also implemented. Extensive testing is employed to show the importance and characteristics of several error resilient tools. Finally we modeled end-to-end RD characteristics to optimize the encoding and protection parameters.

Technology is integrated into daily life more than before as it evolves through communication area. In the past, it started with audio devices that help us to communicate while far between two ends of communication line. Nowadays visual communication comes in front considering the communication technology. This became possible with the improvement in the compression techniques of visual data and increasing speed, optimized architecture of the new family processors. These type processors are named as Digital Signal Processors (DSP&rsquo / s). Texas Instruments TMS320C6000 Digital Signal Processor family offers one of the fastest DSP core in the market. TMS320C64x sub-family processors are newly developed under the TMS320C6000 family to overcome disadvantages of its predecessor family TMS320C62x. TMS320C64x family has optimized architecture for packed data processing, improved data paths and functional units,improved memory architecture and increased speed. These capabilities make this family of processors good candidate for real-time video processing applications. Advantages of this core are used for implementing newly established H.264 Recommendation. Highly optimizing C Compiler of TMS320C64x enabled fast running implementation of encoder blocks that bring heavy computational load to encoder. Such as fast implementation of Motion Estimation, Transform, Entropy Coding became possible. Simplified Densely Centered Uniform-P Search algorithm is used for fast estimation of motion vectors. Time taking parts enhanced to improve the performance of the encoder.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 163-177). Also available on the Internet.