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Advanced intra prediction techniques for image and video coding.

机译：用于图像和视频编码的高级帧内预测技术。

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摘要

Intra prediction has been used in the H.264/AVC video coding standard to improve the coding efficiency of the intra frame. We present different intra prediction techniques that outperform the existing ones adopted by H.264/AVC and JPEG-LS in this research: (1) joint block/line-based intra prediction (JBLIP), (2) hierarchical (or multi-resolution) intra prediction (HIP), and (3) context-based hierarchical intra prediction (CHIP).;We consider two image/video coding scenarios: lossy compression and lossless compression. For lossy compression, we conduct a comprhensive study and show that the existing line-based prediction (LIP) technique adopted by the H.264/AVC standard can only be effective in smooth and simple edge regions. However, it is not as useful in predicting complex regions that contain texture patterns. To overcome this difficulty, we propose a JBLIP scheme with 2D geometrical manipulation to improve coding efficiency. The complexity of the JBLIP scheme is however quite hight due to the need to search the best matched block for the prediction purpose. Thus, we propose a fast search algorithm to reduce the coding complexity. The proposed JBLIP scheme outperforms the LIP scheme in H.264/AVC by up to 1.68dB in the PSNR improvement at the same bit rate.;Next, for lossless compression, we present an advanced intra frame coding using a hierarchical (or multi-resolution) approach called HIP. The objective is to support lossless image/video compression with spatial scalability. We analyze the characteristics of the underlying input signal characteristics and previously proposed signal modeling algorithms and show that most of the existing signal models cannot capture the dynamic signal characteristics through one fixed model. Hence, we propose a spatially scalable intra-prediction scheme that decompose signals according to their characteristics in the frequency domain. A block-based linear combination with edge detection and training set optimization is used to improve coding efficiency for complex textured areas in the EL. It is shown by experimental results the proposed lossless HIP scheme outperforms the lossless LIP scheme of H.264/AVC and JPEG-LS by a bit rate saving of 10%.;Finally, we analyze the inefficiency of the proposed lossless HIP scheme and present an enhanced hierarchical intra prediction coding called the context-based hierarchical intra prediction (CHIP). To save bits for the coding of modes, we propose a mode estimation scheme. To improve prediction accuracy, we employ the principal components analysis (PCA) to extract dominant features from the coarse representation of the base layer. The extracted features are clustered using a k-means clustering algorithm. Then, the context-based interlayer prediction (CIP) scheme is used to select the best prediction candidate without any side information. To enhance coding efficiency furthermore, an adaptive precoding process is performed by analyzing the characteristics of the prediction residual signal and a more accurate approach is proposed to estimate the context model. Experimental results show that the proposed lossless CHIP scheme outperforms the lossless LIP scheme of H.264/AVC and JPEG-LS by 16% in the bit rate saving.
机译：在H.264 / AVC视频编码标准中已经使用帧内预测来提高帧内编码的效率。我们提出了优于本研究中H.264 / AVC和JPEG-LS采用的现有帧内预测技术的不同技术：（1）联合块/基于行的帧内预测（JBLIP），（2）分层（或多分辨率） ）帧内预测（HIP），以及（3）基于上下文的分层帧内预测（CHIP）。；我们考虑两种图像/视频编码方案：有损压缩和无损压缩。对于有损压缩，我们进行了全面的研究，结果表明，H.264 / AVC标准采用的现有基于行的预测（LIP）技术只能在平滑和简单的边缘区域有效。但是，它在预测包含纹理图案的复杂区域时没有用。为了克服这个困难，我们提出了一种具有2D几何操作的JBLIP方案，以提高编码效率。然而，由于需要出于预测目的而搜索最佳匹配的块，因此JBLIP方案的复杂度非常高。因此，我们提出了一种快速搜索算法来降低编码复杂度。拟议的JBLIP方案在相同比特率下的PSNR改善方面比H.264 / AVC中的LIP方案高出1.68dB。接下来，对于无损压缩，我们提出了一种使用分层（或多分辨率）方法称为HIP。目的是支持具有空间可伸缩性的无损图像/视频压缩。我们分析了基础输入信号特征和先前提出的信号建模算法的特征，并表明大多数现有信号模型无法通过一个固定模型捕获动态信号特征。因此，我们提出了一种空间可伸缩的帧内预测方案，该方案可根据信号在频域中的特征对其进行分解。具有边缘检测和训练集优化的基于块的线性组合用于提高EL中复杂纹理区域的编码效率。实验结果表明，所提出的无损HIP方案比H.264 / AVC和JPEG-LS的无损LIP方案节省了10％的比特率。最后，我们分析了所提出的无损HIP方案的低效率，并提出了解决方案。一种增强的分层帧内预测编码，称为基于上下文的分层帧内预测（CHIP）。为了节省用于模式编码的比特，我们提出了一种模式估计方案。为了提高预测精度，我们使用主成分分析（PCA）从基础层的粗略表示中提取主要特征。使用k均值聚类算法对提取的特征进行聚类。然后，基于上下文的层间预测（CIP）方案用于选择没有任何辅助信息的最佳预测候选。为了进一步提高编码效率，通过分析预测残差信号的特征来执行自适应预编码过程，并且提出了一种更准确的方法来估计上下文模型。实验结果表明，所提出的无损CHIP方案在节省比特率方面优于H.264 / AVC和JPEG-LS的无损LIP方案。

著录项

  • 作者

    Dai, Yunyang.;

  • 作者单位

    University of Southern California.;

  • 授予单位 University of Southern California.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 142 p.
  • 总页数 142
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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