HIGH-THROUGHPUT AREA-EFFICIENT INTEGER TRANSFORMS FOR VIDEO CODING

Ph.DDOCTOR OF PHILOSOPH

HEVCのイントラ予測と画素適応オフセット推定の集積回路設計および圧縮センシングへの拡張

早大学位記番号:新7981早稲田大

Algoritmo de estimação de movimento e sua arquitetura de hardware para HEVC

Doutoramento em Engenharia EletrotécnicaVideo coding has been used in applications like video surveillance, video conferencing, video streaming, video broadcasting and video storage. In a typical video coding standard, many algorithms are combined to compress a video. However, one of those algorithms, the motion estimation is the most complex task. Hence, it is necessary to implement this task in real time by using appropriate VLSI architectures. This thesis proposes a new fast motion estimation algorithm and its implementation in real time. The results show that the proposed algorithm and its motion estimation hardware architecture out performs the state of the art. The proposed architecture operates at a maximum operating frequency of 241.6 MHz and is able to process 1080p@60Hz with all possible variables block sizes specified in HEVC standard as well as with motion vector search range of up to ±64 pixels.A codificação de vídeo tem sido usada em aplicações tais como, vídeovigilância, vídeo-conferência, video streaming e armazenamento de vídeo. Numa norma de codificação de vídeo, diversos algoritmos são combinados para comprimir o vídeo. Contudo, um desses algoritmos, a estimação de movimento é a tarefa mais complexa. Por isso, é necessário implementar esta tarefa em tempo real usando arquiteturas de hardware apropriadas. Esta tese propõe um algoritmo de estimação de movimento rápido bem como a sua implementação em tempo real. Os resultados mostram que o algoritmo e a arquitetura de hardware propostos têm melhor desempenho que os existentes. A arquitetura proposta opera a uma frequência máxima de 241.6 MHz e é capaz de processar imagens de resolução 1080p@60Hz, com todos os tamanhos de blocos especificados na norma HEVC, bem como um domínio de pesquisa de vetores de movimento até ±64 pixels

Quality of Experience in Immersive Video Technologies

Over the last decades, several technological revolutions have impacted the television industry, such as the shifts from black & white to color and from standard to high-definition. Nevertheless, further considerable improvements can still be achieved to provide a better multimedia experience, for example with ultra-high-definition, high dynamic range & wide color gamut, or 3D. These so-called immersive technologies aim at providing better, more realistic, and emotionally stronger experiences. To measure quality of experience (QoE), subjective evaluation is the ultimate means since it relies on a pool of human subjects. However, reliable and meaningful results can only be obtained if experiments are properly designed and conducted following a strict methodology. In this thesis, we build a rigorous framework for subjective evaluation of new types of image and video content. We propose different procedures and analysis tools for measuring QoE in immersive technologies. As immersive technologies capture more information than conventional technologies, they have the ability to provide more details, enhanced depth perception, as well as better color, contrast, and brightness. To measure the impact of immersive technologies on the viewersâ QoE, we apply the proposed framework for designing experiments and analyzing collected subjectsâ ratings. We also analyze eye movements to study human visual attention during immersive content playback. Since immersive content carries more information than conventional content, efficient compression algorithms are needed for storage and transmission using existing infrastructures. To determine the required bandwidth for high-quality transmission of immersive content, we use the proposed framework to conduct meticulous evaluations of recent image and video codecs in the context of immersive technologies. Subjective evaluation is time consuming, expensive, and is not always feasible. Consequently, researchers have developed objective metrics to automatically predict quality. To measure the performance of objective metrics in assessing immersive content quality, we perform several in-depth benchmarks of state-of-the-art and commonly used objective metrics. For this aim, we use ground truth quality scores, which are collected under our subjective evaluation framework. To improve QoE, we propose different systems for stereoscopic and autostereoscopic 3D displays in particular. The proposed systems can help reducing the artifacts generated at the visualization stage, which impact picture quality, depth quality, and visual comfort. To demonstrate the effectiveness of these systems, we use the proposed framework to measure viewersâ preference between these systems and standard 2D & 3D modes. In summary, this thesis tackles the problems of measuring, predicting, and improving QoE in immersive technologies. To address these problems, we build a rigorous framework and we apply it through several in-depth investigations. We put essential concepts of multimedia QoE under this framework. These concepts not only are of fundamental nature, but also have shown their impact in very practical applications. In particular, the JPEG, MPEG, and VCEG standardization bodies have adopted these concepts to select technologies that were proposed for standardization and to validate the resulting standards in terms of compression efficiency