Computational Complexity Optimization on H.264 Scalable/Multiview Video Coding

The H.264/MPEG-4 Advanced Video Coding (AVC) standard is a high efficiency and flexible video coding standard compared to previous standards. The high efficiency is achieved by utilizing a comprehensive full search motion estimation method. Although the H.264 standard improves the visual quality at low bitrates, it enormously increases the computational complexity. The research described in this thesis focuses on optimization of the computational complexity on H.264 scalable and multiview video coding. Nowadays, video application areas range from multimedia messaging and mobile to high definition television, and they use different type of transmission systems. The Scalable Video Coding (SVC) extension of the H.264/AVC standard is able to scale the video stream in order to adapt to a variety of devices with different capabilities. Furthermore, a rate control scheme is utilized to improve the visual quality under the constraints of capability and channel bandwidth. However, the computational complexity is increased. A simplified rate control scheme is proposed to reduce the computational complexity. In the proposed scheme, the quantisation parameter can be computed directly instead of using the exhaustive Rate-Quantization model. The linear Mean Absolute Distortion (MAD) prediction model is used to predict the scene change, and the quantisation parameter will be increased directly by a threshold when the scene changes abruptly; otherwise, the comprehensive Rate-Quantisation model will be used. Results show that the optimized rate control scheme is efficient on time saving. Multiview Video Coding (MVC) is efficient on reducing the huge amount of data in multiple-view video coding. The inter-view reference frames from the adjacent views are exploited for prediction in addition to the temporal prediction. However, due to the increase in the number of reference frames, the computational complexity is also increased. In order to manage the reference frame efficiently, a phase correlation algorithm is utilized to remove the inefficient inter-view reference frame from the reference list. The dependency between the inter-view reference frame and current frame is decided based on the phase correlation coefficients. If the inter-view reference frame is highly related to the current frame, it is still enabled in the reference list; otherwise, it will be disabled. The experimental results show that the proposed scheme is efficient on time saving and without loss in visual quality and increase in bitrate. The proposed optimization algorithms are efficient in reducing the computational complexity on H.264/AVC extension. The low computational complexity algorithm is useful in the design of future video coding standards, especially on low power handheld devices

Efficient algorithms for scalable video coding

A scalable video bitstream specifically designed for the needs of various client terminals, network conditions, and user demands is much desired in current and future video transmission and storage systems. The scalable extension of the H.264/AVC standard (SVC) has been developed to satisfy the new challenges posed by heterogeneous environments, as it permits a single video stream to be decoded fully or partially with variable quality, resolution, and frame rate in order to adapt to a specific application. This thesis presents novel improved algorithms for SVC, including: 1) a fast inter-frame and inter-layer coding mode selection algorithm based on motion activity; 2) a hierarchical fast mode selection algorithm; 3) a two-part Rate Distortion (RD) model targeting the properties of different prediction modes for the SVC rate control scheme; and 4) an optimised Mean Absolute Difference (MAD) prediction model. The proposed fast inter-frame and inter-layer mode selection algorithm is based on the empirical observation that a macroblock (MB) with slow movement is more likely to be best matched by one in the same resolution layer. However, for a macroblock with fast movement, motion estimation between layers is required. Simulation results show that the algorithm can reduce the encoding time by up to 40%, with negligible degradation in RD performance. The proposed hierarchical fast mode selection scheme comprises four levels and makes full use of inter-layer, temporal and spatial correlation aswell as the texture information of each macroblock. Overall, the new technique demonstrates the same coding performance in terms of picture quality and compression ratio as that of the SVC standard, yet produces a saving in encoding time of up to 84%. Compared with state-of-the-art SVC fast mode selection algorithms, the proposed algorithm achieves a superior computational time reduction under very similar RD performance conditions. The existing SVC rate distortion model cannot accurately represent the RD properties of the prediction modes, because it is influenced by the use of inter-layer prediction. A separate RD model for inter-layer prediction coding in the enhancement layer(s) is therefore introduced. Overall, the proposed algorithms improve the average PSNR by up to 0.34dB or produce an average saving in bit rate of up to 7.78%. Furthermore, the control accuracy is maintained to within 0.07% on average. As aMADprediction error always exists and cannot be avoided, an optimisedMADprediction model for the spatial enhancement layers is proposed that considers the MAD from previous temporal frames and previous spatial frames together, to achieve a more accurateMADprediction. Simulation results indicate that the proposedMADprediction model reduces the MAD prediction error by up to 79% compared with the JVT-W043 implementation

Improving the quality of H.264/AVC by using a new Rate-Quantization model

International audienceRate control plays a key role in video coding standards. Its goal is to achieve a good quality at a given target bit-rate. In H.264/AVC, rate control algorithm for both Intra and Inter-frames suffers from some defects. In the Intra-frame rate control, the initial quantization parameter (QP) is mainly adjusted according to a global target bit-rate and length of GOP. This determination is inappropriate and generates errors in the whole of video sequence. For Inter coding unit (Frame or Macroblock), the use of MAD (Mean Average Differences) as a complexity measure, remains inefficient, resulting in improper QP values because the MAD handles locally images characteristics. QP miscalculations may also result from the linear prediction model which assumes similar complexity from coding unit to another. To overcome these defects, we propose in this paper, a new Rate-Quantization (R-Q) model resulting from extensive experiments. This latter is divided into two models. The first one is an Intra R-Q model used to determine an optimal initial quantization parameter for Intra-frames. The second one is an Inter R-Q model that aims at determining the QP of Inter coding unit according to the statistics of the previous coded ones. It does not use any complexity measure and substitutes both linear and quadratic models used in H.264/AVC rate controller. Objective and subjective simulations have been carried out using JM15.0 reference software. Compared to this latter, the global R-Q model (Intra and Inter models combined) improves the coding efficiency in terms of PSNR, objectively (up to +2.01dB), subjectively (by psychophysical experiments) and in terms of computational complexity

Mode decision for the H.264/AVC video coding standard

H.264/AVC video coding standard gives us a very promising future for the field of video broadcasting and communication because of its high coding efficiency compared with other older video coding standards. However, high coding efficiency also carries high computational complexity. Fast motion estimation and fast mode decision are two very useful techniques which can significantly reduce computational complexity. This thesis focuses on the field of fast mode decision. The goal of this thesis is that for very similar RD performance compared with H.264/AVC video coding standard, we aim to find new fast mode decision techniques which can afford significant time savings. [Continues.

Investigating low-bitrate, low-complexity H.264 region of interest techniques in error-prone environments

The H.264/AVC video coding standard leverages advanced compression methods to provide a significant increase in performance over previous CODECs in terms of picture quality, bitrate, and flexibility. The specification itself provides several profiles and levels that allow customization through the use of various advanced features. In addition to these features, several new video coding techniques have been developed since the standard\u27s inception. One such technique known as Region of Interest (RoI) coding has been in existence since before H.264\u27s formalization, and several means of implementing RoI coding in H.264 have been proposed. Region of Interest coding operates under the assumption that one or more regions of a sequence have higher priority than the rest of the video. One goal of RoI coding is to provide a decrease in bitrate without significant loss of perceptual quality, and this is particularly applicable to low complexity environments, if the proper implementation is used. Furthermore, RoI coding may allow for enhanced error resilience in the selected regions if desired, making RoI suitable for both low-bitrate and error-prone scenarios. The goal of this thesis project was to examine H.264 Region of Interest coding as it applies to such scenarios. A modified version of the H.264 JM Reference Software was created in which all non-Baseline profile features were removed. Six low-complexity RoI coding techniques, three targeting rate control and three targeting error resilience, were selected for implementation. Error and distortion modeling tools were created to enhance the quality of experimental data. Results were gathered by varying a range of coding parameters including frame size, target bitrate, and macroblock error rates. Methods were then examined based on their rate-distortion curves, ability to achieve target bitrates accurately, and per-region distortions where applicable

Efficient Region-of-Interest Scalable Video Coding with Adaptive Bit-Rate Control

This work relates to the regions-of-interest (ROI) coding that is a desirable feature in future applications based on the scalable video coding, which is an extension of the H.264/MPEG-4 AVC standard. Due to the dramatic technological progress, there is a plurality of heterogeneous devices, which can be used for viewing a variety of video content. Devices such as smartphones and tablets are mostly resource-limited devices, which make it difficult to display high-quality content. Usually, the displayed video content contains one or more ROI(s), which should be adaptively selected from the preencoded scalable video bitstream. Thus, an efficient scalable ROI video coding scheme is proposed in this work, thereby enabling the extraction of the desired regions-of-interest and the adaptive setting of the desirable ROI location, size, and resolution. In addition, an adaptive bit-rate control is provided for the region-of-interest scalable video coding. The performance of the presented techniques is demonstrated and compared with the joint scalable video model reference software (JSVM 9.19), thereby showing significant bit-rate savings as a tradeoff for the relatively low PSNR degradation

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