High-Level Synthesis Based VLSI Architectures for Video Coding

High Efficiency Video Coding (HEVC) is state-of-the-art video coding standard. Emerging applications like free-viewpoint video, 360degree video, augmented reality, 3D movies etc. require standardized extensions of HEVC. The standardized extensions of HEVC include HEVC Scalable Video Coding (SHVC), HEVC Multiview Video Coding (MV-HEVC), MV-HEVC+ Depth (3D-HEVC) and HEVC Screen Content Coding. 3D-HEVC is used for applications like view synthesis generation, free-viewpoint video. Coding and transmission of depth maps in 3D-HEVC is used for the virtual view synthesis by the algorithms like Depth Image Based Rendering (DIBR). As first step, we performed the profiling of the 3D-HEVC standard. Computational intensive parts of the standard are identified for the efficient hardware implementation. One of the computational intensive part of the 3D-HEVC, HEVC and H.264/AVC is the Interpolation Filtering used for Fractional Motion Estimation (FME). The hardware implementation of the interpolation filtering is carried out using High-Level Synthesis (HLS) tools. Xilinx Vivado Design Suite is used for the HLS implementation of the interpolation filters of HEVC and H.264/AVC. The complexity of the digital systems is greatly increased. High-Level Synthesis is the methodology which offers great benefits such as late architectural or functional changes without time consuming in rewriting of RTL-code, algorithms can be tested and evaluated early in the design cycle and development of accurate models against which the final hardware can be verified

Motion compensation with minimal residue dispersion matching criteria

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnoloigia, 2016.Com a crescente demanda por serviços de vídeo, técnicas de compressão de vídeo tornaram-se uma tecnologia de importância central para os sistemas de comunicação modernos. Padrões para codificação de vídeo foram criados pela indústria, permitindo a integração entre esses serviços e os mais diversos dispositivos para acessá-los. A quase totalidade desses padrões adota um modelo de codificação híbrida, que combina métodos de codificação diferencial e de codificação por transformadas, utilizando a compensação de movimento por blocos (CMB) como técnica central na etapa de predição. O método CMB tornou-se a mais importante técnica para explorar a forte redundância temporal típica da maioria das sequências de vídeo. De fato, muito do aprimoramento em termos de e ciência na codificação de vídeo observado nas últimas duas décadas pode ser atribuído a refinamentos incrementais na técnica de CMB. Neste trabalho, apresentamos um novo refinamento a essa técnica. Uma questão central à abordagem de CMB é a estimação de movimento (EM), ou seja, a seleção de vetores de movimento (VM) apropriados. Padrões de codificação tendem a regular estritamente a sintaxe de codificação e os processos de decodificação para VM's e informação de resíduo, mas o algoritmo de EM em si é deixado a critério dos projetistas do codec. No entanto, embora praticamente qualquer critério de seleção permita uma decodi cação correta, uma seleção de VM criteriosa é vital para a e ciência global do codec, garantindo ao codi cador uma vantagem competitiva no mercado. A maioria do algoritmos de EM baseia-se na minimização de uma função de custo para os blocos candidatos a predição para um dado bloco alvo, geralmente a soma das diferenças absolutas (SDA) ou a soma das diferenças quadradas (SDQ). A minimização de qualquer uma dessas funções de custo selecionará a predição que resulta no menor resíduo, cada uma em um sentido diferente porém bem de nido. Neste trabalho, mostramos que a predição de mínima dispersão de resíduo é frequentemente mais e ciente que a tradicional predição com resíduo de mínimo tamanho. Como prova de conceito, propomos o algoritmo de duplo critério de correspondência (ADCC), um algoritmo simples em dois estágios para explorar ambos esses critérios de seleção em turnos. Estágios de minimização de dispersão e de minimização de tamanho são executadas independentemente. O codificador então compara o desempenho dessas predições em termos da relação taxa-distorção e efetivamente codifica somente a mais eficiente. Para o estágio de minimização de dispersão do ADCC, propomos ainda o desvio absoluto total com relação à média (DATM) como a medida de dispersão a ser minimizada no processo de EM. A tradicional SDA é utilizada como a função de custo para EM no estágio de minimização de tamanho. O ADCC com SDA/DATM foi implementado em uma versão modificada do software de referência JM para o amplamente difundido padrão H.264/AVC de codificação. Absoluta compatibilidade a esse padrão foi mantida, de forma que nenhuma modificação foi necessária no lado do decodificador. Os resultados mostram aprimoramentos significativos com relação ao codificador H.264/AVC não modificado.With the ever growing demand for video services, video compression techniques have become a technology of central importance for communication systems. Industry standards for video coding have emerged, allowing the integration between these services and the most diverse devices. The almost entirety of these standards adopt a hybrid coding model combining di erential and transform coding methods, with block-based motion compensation (BMC) at the core of its prediction step. The BMC method have become the single most important technique to exploit the strong temporal redundancy typical of most video sequences. In fact, much of the improvements in video coding e ciency over the past two decades can be attributed to incremental re nements to the BMC technique. In this work, we propose another such re nement. A key issue to the BMC framework is motion estimation (ME), i.e., the selection of appropriate motion vectors (MV). Coding standards tend to strictly regulate the coding syntax and decoding processes for MV's and residual information, but the ME algorithm itself is left at the discretion of the codec designers. However, though virtually any MV selection criterion will allow for correct decoding, judicious MV selection is critical to the overall codec performance, providing the encoder with a competitive edge in the market. Most ME algorithms rely on the minimization of a cost function for the candidate prediction blocks given a target block, usually the sum of absolute di erences (SAD) or the sum of squared di erences (SSD). The minimization of any of these cost functions will select the prediction that results in the smallest residual, each in a di erent but well de ned sense. In this work, we show that the prediction of minimal residue dispersion is frequently more e cient than the usual prediction of minimal residue size. As proof of concept, we propose the double matching criterion algorithm (DMCA), a simple two-pass algorithm to exploit both of these MV selection criteria in turns. Dispersion minimizing and size minimizing predictions are carried out independently. The encoder then compares these predictions in terms of rate-distortion performance and outputs only the most e cient one. For the dispersion minimizing pass of the DMCA, we also propose the total absolute deviation from the mean (TADM) as the measure of residue dispersion to be minimized in ME. The usual SAD is used as the ME cost function in the size minimizing pass. The DMCA with SAD/TADM was implemented in a modi ed version of the JM reference software encoder for the widely popular H.264/AVC coding standard. Absolute compliance to the standard was maintained, so that no modi cations on the decoder side were necessary. Results show signi cant improvements over the unmodi ed H.264/AVC encoder

Audio/Video Transmission over IEEE 802.11e Networks: Retry Limit Adaptation and Distortion Estimation

The objective of this thesis focuses on the audio and video transmission over wireless networks adopting the family of the IEEE 802.11x standards. In particular, this thesis discusses about the resolution of four issues: the adaptive retransmission, the comparison of video quality indexes for retry limit adaptation purposes, the estimation of the distortion and the joint adaptation of the maximum number of retransmissions of voice and video flows

Contributions to reconfigurable video coding and low bit rate video coding

In this PhD Thesis, two different issues on video coding are stated and their corresponding proposed solutions discussed. In the first place, some problems of the use of video coding standards are identi ed and the potential of new reconfigurable platforms is put to the test. Specifically, the proposal from MPEG for a Reconfigurable Video Coding (RVC) standard is compared with a more ambitious proposal for Fully Configurable Video Coding (FCVC). In both cases, the objective is to nd a way for the definition of new video codecs without the concurrence of a classical standardization process, in order to reduce the time-to-market of new ideas while maintaining the proper interoperability between codecs. The main difference between these approaches is the ability of FCVC to reconfigure each program line in the encoder and decoder definition, while RVC only enables to conform the codec description from a database of standardized functional units. The proof of concept carried out in the FCVC prototype enabled to propose the incorporation of some of the FCVC capabilities in future versions of the RVC standard. The second part of the Thesis deals with the design and implementation of a filtering algorithm in a hybrid video encoder in order to simplify the high frequencies present in the prediction residue, which are the most expensive for the encoder in terms of output bit rate. By means of this filtering, the quantization scale employed by the video encoder in low bit rate is kept in reasonable values and the risk of appearance of encoding artifacts is reduced. The proposed algorithm includes a block for filter control that determines the proper amount of filtering from the encoder operating point and the characteristics of the sequence to be processed. This filter control is tuned according to perceptual considerations related with overall subjective quality assessment. Finally, the complete algorithm was tested by means of a standard subjective video quality assessment test, and the results showed a noticeable improvement in the quality score with respect to the non-filtered version, confirming that the proposed method reduces the presence of harmful low bit rate artifacts

No-reference Bitstream-layer Model for Perceptual Quality Assessment of V-PCC Encoded Point Clouds

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.No-reference bitstream-layer models for point cloud quality assessment (PCQA) use the information extracted from a bitstream for real-time and nonintrusive quality monitoring. We propose a no-reference bitstream-layer model for the perceptual quality assessment of video-based point cloud compression (V-PCC) encoded point clouds. First, we describe the fundamental relationship between perceptual coding distortion and the texture quantization parameter (TQP) when geometry encoding is lossless. Then, we incorporate the texture complexity (TC) into the proposed model while considering the fact that the perceptual coding distortion of a point cloud depends on the texture characteristics. TC is estimated using TQP and the texture bitrate per pixel (TBPP), both of which are extracted from the compressed bitstream without resorting to complete decoding. Then, we construct a texture distortion assessment model upon TQP and TBPP. By combining this texture distortion model with the geometry quantization parameter (GQP), we obtain an overall no-reference bitstream-layer PCQA model that we call bitstreamPCQ. Experimental results show that the proposed model markedly outperforms existing models in terms of widely used performance criteria, including the Pearson linear correlation coefficient (PLCC), the Spearman rank order correlation coefficient (SRCC) and the root mean square error (RMSE). The dataset developed in this study is publicly available at https://github.com/qdushl/Waterloo-Point-Cloud-Database-3.0

Low complexity in-loop perceptual video coding

The tradition of broadcast video is today complemented with user generated content, as portable devices support video coding. Similarly, computing is becoming ubiquitous, where Internet of Things (IoT) incorporate heterogeneous networks to communicate with personal and/or infrastructure devices. Irrespective, the emphasises is on bandwidth and processor efficiencies, meaning increasing the signalling options in video encoding. Consequently, assessment for pixel differences applies uniform cost to be processor efficient, in contrast the Human Visual System (HVS) has non-uniform sensitivity based upon lighting, edges and textures. Existing perceptual assessments, are natively incompatible and processor demanding, making perceptual video coding (PVC) unsuitable for these environments. This research allows existing perceptual assessment at the native level using low complexity techniques, before producing new pixel-base image quality assessments (IQAs). To manage these IQAs a framework was developed and implemented in the high efficiency video coding (HEVC) encoder. This resulted in bit-redistribution, where greater bits and smaller partitioning were allocated to perceptually significant regions. Using a HEVC optimised processor the timing increase was < +4% and < +6% for video streaming and recording applications respectively, 1/3 of an existing low complexity PVC solution. Future work should be directed towards perceptual quantisation which offers the potential for perceptual coding gain