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Rate-distortion Optimization Techniques for 2D and 3D Video Coding.

机译：2D和3D视频编码的速率失真优化技术。

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摘要

Video coding is the process of compressing and decompressing a 2D digital video signal, which is widely used in broadcasting TV, terrestrial TV, video streaming, video conferencing and DVD applications. The benefits of improving the coding efficiency are obvious in the sense that it will reduce the bandwidth for transmitting the compressed signal, save the storage memory size and improve the visual quality under the same bitrate. To improve the coding efficiency, rate-distortion optimization techniques are widely used in image and video compression systems, which are concerned with the task of representing a source with as few bits as possible, for a given fidelity constraint. In practice, the constrained rate-distortion optimization problem is formulated as an unconstrained Lagrangian minimization problem, which is used to evaluate the performance of each possible coding mode.;In this thesis, we address the problems of intra prediction, intra transform coding and quantization in the traditional 2D video coding framework, and interview prediction in the 3D video coding framework from the perspective of rate distortion optimization. First, an edge-based adaptive directional intra prediction is proposed to reduce the residue energy for edge rich regions. Starting from the nature of traditional block based intra prediction, the residue characteristics are experimentally analyzed. It is pointed out that traditional block based intra prediction fails to predict the edge region with high prediction accuracy. To solve this problem, an edge model is established within a block and the model parameters are determined using the rate distortion optimization criteria.;Next, the intra transform coding is investigated. After intra prediction, residue is formed by subtracting the predictor from the original signal and transform coding is applied to the residue. To further improve the coding efficiency of intra transform coding, a rate-distortion cost function is established to estimate the practical rate-distortion cost. Through minimizing the proposed cost function, we put forward a novel rate-distortion optimized transform (RDOT) scheme which allows a set of specially trained transforms to be available to all modes, and each block can choose its preferred transform to minimize the rate-distortion cost. The optimization can be solved using the Lloyd-type algorithm (a sequence of transform optimization and data reclassification alternately) to find the optimal set of transforms.;Further, we address the scalar quantization in intra frame coding. After transform, the transformed coefficients are quantized using scaler quantizer. We examine and analyze the statistical properties of transformed coefficients of different intra prediction modes, and derive an optimal quantization matrix, such that the total rate is minimized under a distortion constraint for each mode.;Besides the intra frame coding, the inter-view coding is discussed in the context of 3D video coding from the perspective of rate distortion optimization. To improve the coding efficiency of 3D coding systems, view synthesis prediction (VSP) is proposed as an alternative non-translational disparity compensated predictor. And it is argued that when we choose the depth derived disparity vector as the motion vector and motion vector predictor, the lower bound of the Lagrangian cost is achieved. And this technique is adopted in the 3D video coding standard 3D-HEVC.;To further increase the usage of VSP, an improved depth coding is proposed by allowing different quantization parameters (QP) for each block according to their content characteristics. And the decision of the depth QP is made according to the rate distortion minimization criteria, where the distortion is measured in terms of both synthesis distortion and depth coding distortion, rather than depth coding distortion alone.
机译：视频编码是对2D数字视频信号进行压缩和解压缩的过程，广泛用于广播电视，地面电视，视频流，视频会议和DVD应用。在降低编码效率的前提下，提高编码效率的好处是显而易见的，因为它将在相同的比特率下减少传输压缩信号的带宽，节省存储空间并提高视觉质量。为了提高编码效率，速率失真优化技术被广泛地用于图像和视频压缩系统中，它们涉及在给定保真度约束下以尽可能少的比特来表示源的任务。在实践中，将约束率失真优化问题表述为无约束拉格朗日最小化问题，用于评估每种可能的编码模式的性能。本文针对帧内预测，​​帧内变换编码和量化问题进行了研究。从传统的2D视频编码框架中进行评估，并从速率失真优化的角度对3D视频编码框架中的采访进行预测。首先，提出了一种基于边缘的自适应方向帧内预测，​​以减少边缘富集区域的残差能量。从传统的基于块的帧内预测的性质开始，对残留特征进行实验分析。要指出的是，传统的基于块的帧内预测不能以高的预测精度来预测边缘区域。为了解决这个问题，在块内建立边缘模型，并使用速率失真优化标准确定模型参数。接下来，研究帧内变换编码。帧内预测之后，通过从原始信号中减去预测变量来形成残差，然后将变换编码应用于残差。为了进一步提高帧内变换编码的编码效率，建立了速率失真代价函数以估计实际的速率失真代价。通过最小化提出的成本函数，我们提出了一种新颖的速率失真优化变换（RDOT）方案，该方案允许一组经过特殊训练的变换可用于所有模式，并且每个块都可以选择其首选的变换以最小化速率失真。成本。可以使用Lloyd型算法（交替进行一系列的变换优化和数据重新分类）找到最优的变换集，从而解决优化问题。此外，我们在帧内编码中解决了标量量化问题。变换后，使用定标器量化器对变换后的系数进行量化。我们检查并分析了不同帧内预测模式的变换系数的统计特性，并得出了一个最佳量化矩阵，从而在每种模式的失真约束下使总速率最小化。除帧内编码外，视图间编码从速率失真优化的角度在3D视频编码的上下文中讨论了这一点。为了提高3D编码系统的编码效率，提出了视图合成预测（VSP）作为替代的非平移视差补偿预测器。有人认为，当我们选择深度导出的视差向量作为运动向量和运动向量预测变量时，可以达到拉格朗日成本的下界。并且在3D视频编码标准3D-HEVC中采用了该技术。为了进一步增加VSP的使用，提出了一种改进的深度编码，其方法是根据每个块的内容特征允许不同的量化参数（QP）。并且，根据速率失真最小化标准来确定深度QP，其中根据合成失真和深度编码失真来测量失真，而不是仅根据深度编码失真来进行失真测量。

著录项

  • 作者

    Zou, Feng.;

  • 作者单位

    Hong Kong University of Science and Technology (Hong Kong).;

  • 授予单位 Hong Kong University of Science and Technology (Hong Kong).;
  • 学科 Engineering Electronics and Electrical.;Computer Science.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 147 p.
  • 总页数 147
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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