A Cauchy-density-based rate controller for H.264/AVC in low-delay environments

The accuracy of the Cauchy probability density function for modeling of the discrete cosine transform coefficient distribution has already been proved for the frame layer of the rate control subsystem of a hybrid video coder. Nevertheless, in some specific applications operating in real-time low-delay environments, a basic unit layer is recommended in order to provide a good trade-off between quality and delay control. In this paper, a novel basic unit bit allocation for H.264/AVC is proposed based on a simplified Cauchy probability density function source modeling. The experimental results show that the proposed algorithm improves the average peak signal-to-noise ratio in 0.28 and 0.35 dB with respect to two well-known rate control schemes, while maintaining similar peak signal-to-noise ratio standard deviation and buffer occupancy evolution

Cauchy-Density-Based Basic Unit Layer Rate Controller for H.264/AVC

The rate control problem has been extensively studied in parallel to the development of the different video coding standards. The bit allocation via Cauchy-density-based rate-distortion (R-D) modeling of the discrete cosine transform (DCT) coefficients has proved to be one of the most accurate solution at picture level. Nevertheless, in some specific applications operating in real-time low-delay environments, a basic unit (BU) layer is recommended in order to provide a good trade-off between picture quality and delay control. In this paper, a novel BU bit allocation for H.264/AVC is proposed based on a simplified Cauchy probability density function (PDF) source modeling. The experimental results are twofold: 1) the proposed rate control algorithm (RCA) achieves an average PSNR improvement of 0.28 dB respect to a well known BU layer RCA, while maintaining a similar buffer occupancy evolution; and 2) It achieves to notably reduce the buffer occupancy fluctuations respect to a well known picture layer RCA, while maintaining similar quality levels.Publicad

A rate control algorithm for scalable video coding

This thesis proposes a rate control (RC) algorithm for H.264/scalable video coding (SVC) specially designed for real-time variable bit rate (VBR) applications with buffer constraints. The VBR controller assumes that consecutive pictures within the same scene often exhibit similar degrees of complexity, and aims to prevent unnecessary quantization parameter (QP) fluctuations by allowing for just an incremental variation of QP with respect to that of the previous picture. In order to adapt this idea to H.264/SVC, a rate controller is located at each dependency layer (spatial or coarse grain scalability) so that each rate controller is responsible for determining the proper QP increment. Actually, one of the main contributions of the thesis is a QP increment regression model that is based on Gaussian processes. This model has been derived from some observations drawn from a discrete set of representative encoding states. Two real-time application scenarios were simulated to assess the performance of the VBR controller with respect to two well-known RC methods. The experimental results show that our proposal achieves an excellent performance in terms of quality consistency, buffer control, adjustment to the target bit rate, and computational complexity. Moreover, unlike typical RC algorithms for SVC that only satisfy the hypothetical reference decoder (HRD) constraints for the highest temporal resolution sub-stream of each dependency layer, the proposed VBR controller also delivers HRD-compliant sub-streams with lower temporal resolutions.To this end, a novel approach that uses a set of buffers (one per temporal resolution sub-stream) within a dependency layer has been built on top of the RC algorithm.The proposed approach aims to simultaneously control the buffer levels for overflow and underflow prevention, while maximizing the reconstructed video quality of the corresponding sub-streams. This in-layer multibuffer framework for rate-controlled SVC does not require additional dependency layers to deliver different HRD-compliant temporal resolutions for a given video source, thus improving the coding e ciency when compared to typical SVC encoder con gurations since, for the same target bit rate, less layers are encoded

Computational inference and control of quality in multimedia services

Quality is the degree of excellence we expect of a service or a product. It is also one of the key factors that determine its value. For multimedia services, understanding the experienced quality means understanding how the delivered delity, precision and reliability correspond to the users' expectations. Yet the quality of multimedia services is inextricably linked to the underlying technology. It is developments in video recording, compression and transport as well as display technologies that enables high quality multimedia services to become ubiquitous. The constant evolution of these technologies delivers a steady increase in performance, but also a growing level of complexity. As new technologies stack on top of each other the interactions between them and their components become more intricate and obscure. In this environment optimizing the delivered quality of multimedia services becomes increasingly challenging. The factors that aect the experienced quality, or Quality of Experience (QoE), tend to have complex non-linear relationships. The subjectively perceived QoE is hard to measure directly and continuously evolves with the user's expectations. Faced with the diculty of designing an expert system for QoE management that relies on painstaking measurements and intricate heuristics, we turn to an approach based on learning or inference. The set of solutions presented in this work rely on computational intelligence techniques that do inference over the large set of signals coming from the system to deliver QoE models based on user feedback. We furthermore present solutions for inference of optimized control in systems with no guarantees for resource availability. This approach oers the opportunity to be more accurate in assessing the perceived quality, to incorporate more factors and to adapt as technology and user expectations evolve. In a similar fashion, the inferred control strategies can uncover more intricate patterns coming from the sensors and therefore implement farther-reaching decisions. Similarly to natural systems, this continuous adaptation and learning makes these systems more robust to perturbations in the environment, longer lasting accuracy and higher eciency in dealing with increased complexity. Overcoming this increasing complexity and diversity is crucial for addressing the challenges of future multimedia system. Through experiments and simulations this work demonstrates that adopting an approach of learning can improve the sub jective and objective QoE estimation, enable the implementation of ecient and scalable QoE management as well as ecient control mechanisms

Algorithms & implementation of advanced video coding standards

Advanced video coding standards have become widely deployed coding techniques used in numerous products, such as broadcast, video conference, mobile television and blu-ray disc, etc. New compression techniques are gradually included in video coding standards so that a 50% compression rate reduction is achievable every five years. However, the trend also has brought many problems, such as, dramatically increased computational complexity, co-existing multiple standards and gradually increased development time. To solve the above problems, this thesis intends to investigate efficient algorithms for the latest video coding standard, H.264/AVC. Two aspects of H.264/AVC standard are inspected in this thesis: (1) Speeding up intra4x4 prediction with parallel architecture. (2) Applying an efficient rate control algorithm based on deviation measure to intra frame. Another aim of this thesis is to work on low-complexity algorithms for MPEG-2 to H.264/AVC transcoder. Three main mapping algorithms and a computational complexity reduction algorithm are focused by this thesis: motion vector mapping, block mapping, field-frame mapping and efficient modes ranking algorithms. Finally, a new video coding framework methodology to reduce development time is examined. This thesis explores the implementation of MPEG-4 simple profile with the RVC framework. A key technique of automatically generating variable length decoder table is solved in this thesis. Moreover, another important video coding standard, DV/DVCPRO, is further modeled by RVC framework. Consequently, besides the available MPEG-4 simple profile and China audio/video standard, a new member is therefore added into the RVC framework family. A part of the research work presented in this thesis is targeted algorithms and implementation of video coding standards. In the wide topic, three main problems are investigated. The results show that the methodologies presented in this thesis are efficient and encourage

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