Novas arquiteturas de hardware desenvolvidas para blocos chave do padrão de codificação de vídeo ISO/IEC 14496-10 são discutidas, propostas, implementadas e validades nesta tese. Também chamado de H.264, AVC (Advanced Video Coder) ou MPEG-4 parte 10, o padrão é o estado da arte em codificação de vídeo, apresentando as mais altas taxas de compressão possíveis por um compressor de vídeo padronizado por organismos internacionais (ISO/IEC e ITU-T). O H.264 já passou por três revisões importantes: na primeira foram incluídos novos perfis, voltados para a extensão da fidelidade e aplicações profissionais, na segunda veio o suporte a escalabilidade (SVC – Scalable Video Coder). Uma terceira revisão suporta fontes de vídeo com múltiplas vistas (MVC – Multi-view Video Coder). Nesta tese são apresentadas arquiteturas para dois módulos do codificador H.264: o CABAC e o Filtro de Deblocagem (Deblocking Filter). O CABAC (Context-Adaptive Binary Arithmetic Coder) possui desafios importantes devido às dependências de dados de natureza bit-a-bit. Uma revisão das alternativas arquiteturais e uma solução específica para a codificação CABAC é apresentada nesta tese. O filtro de deblocagem também apresenta diversos desafios importantes para seu desenvolvimento e foi alvo de uma proposta arquitetural apresentada neste trabalho. Finalmente a arquitetura de uma plataforma de validação genérica para validar módulos desenvolvidos para o codificador e decodificador H.264 também é apresentada. Os módulos escolhidos estão de acordo com os demais trabalhos realizados pelo grupo de pesquisa da UFRGS, que têm por objetivo desenvolver um decodificador e um codificador completos capazes de processar vídeo digital de alta definição no formato 1080p em tempo real. / New hardware architectures developed for key blocks of the ISO/IEC 14496-10 video coding standard are discussed, proposed, implemented, and validated in this thesis. The standard is also called H.264, AVC (Advanced Video Coder) or MPEG-4 part 10, and is the state-of-the-art in video coding, presenting the highest compression ratios achievable by an internationally standardized video coder (ISO/IEC and ITU-T). The H.264 has already been revised three times: the first included new profiles for fidelity extension and professional applications. The second brought the scalability support (SVC – Scalable Video Coder). The third revision supports video sources with multiple views (MVC – Multi-view Video Coder). The present work developed high performance architectures for CABAC (Context-Adaptive Binary Arithmetic Coder), which were challenging because of the bitwise data dependencies. A through revision of the alternative architectures and a specific architectural solution for CABAC encoding are presented in this thesis. A dedicated hardware architecture for a HIGH profile Deblocking Filter is also presented, developed, validated and synthesized for two different targets: FPGA and ASIC. The validation methodology is presented and applied to three different modules of the H.264 encoder. The H.264 blocks dealt with in this thesis work complement those developed by other works in the UFRGS research group and contribute to the development of complete encoders for real-time processing of high definition digital video at 1080p.

Mobile devices such as PDAs and cellular phones became indispensible part of business and entertainment world. There are a number of applications run on these devices and they tend to increase day by day causing devices tend to consume more battery power. H.264/AVC is an emerging video compression standard that is likely to be used widely in multimedia environments. As a mobile application, video compression algorithm of H.264 standard has a complex structure that increase the power demand of realizing hardware. In order to reduce this power demand, power consuming parts of the algorithm like deblocking filter and transform&amp / quantization need to be specifically changed for low power application. A low power deblocking filter and inverse transform/quantization algorithm for H.264/AVC decoder is to be proposed and implemented on FPGA.

The use of audio and video communication has increased exponentially over the last decade and has gone from speech over GSM to HD resolution video conference between continents on mobile devices. As the use becomes more widespread the interest in delivering high quality media increases even on devices with limited resources. This includes both development and enhancement of the communication chain but also the topic of objective measurements of the perceived quality. The focus of this thesis work has been to perform enhancement within speech encoding and video decoding, to measure influence factors of audio and video performance, and to build methods to predict the perceived video quality. The audio enhancement part of this thesis addresses the well known problem in the GSM system with an interfering signal generated by the switching nature of TDMA cellular telephony. Two different solutions are given to suppress such interference internally in the mobile handset. The first method involves the use of subtractive noise cancellation employing correlators, the second uses a structure of IIR notch filters. Both solutions use control algorithms based on the state of the communication between the mobile handset and the base station. The video enhancement part presents two post-filters. These two filters are designed to improve visual quality of highly compressed video streams from standard, block-based video codecs by combating both blocking and ringing artifacts. The second post-filter also performs sharpening. The third part addresses the problem of measuring audio and video delay as well as skewness between these, also known as synchronization. This method is a black box technique which enables it to be applied on any audiovisual application, proprietary as well as open standards, and can be run on any platform and over any network connectivity. The last part addresses no-reference (NR) bitstream video quality prediction using features extracted from the coded video stream. Several methods have been used and evaluated: Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Least Square Support Vector Machines (LS-SVM), showing high correlation with both MOS and objective video assessment methods as PSNR and PEVQ. The impact from temporal, spatial and quantization variations on perceptual video quality has also been addressed, together with the trade off between these, and for this purpose a set of locally conducted subjective experiments were performed.