视频压缩编码的运动估计与补偿技术
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摘要
本文主要讨论视频压缩编码的运动估计与补偿技术,方块匹配方法(BMA)在非平移运动情况下的预测误差较大,同时占用编码器一半以上的运算量。本文首先讨论运动估计的快速计算方法,然后提出可变形块匹配算法(DBMA),提高运动估计的准确性。
本文介绍了人眼视觉系统生理特性和视频压缩编码的理论基础,指出视频压缩的基本方法和运动估计与补偿的关键作用;介绍了视频压缩编码的系统结构,总结并比较现有的各种视频压缩编码标准,说明运动估计在实际编码系统中的使用方法及发展过程;分析真实场景的运动变化在二维图像上的参数表示方法,并概括介绍各种运动估计方法。
为了降低现行系统中使用的BMA的复杂度,本文首先介绍几种有代表性的快速算法,全面总结了视频信号属性和运动场的分布特征,详细分析利用信号特征加快BMA的方法,在理论分析基础上提出自适应快速搜索算法(APFS),在相近预测质量的条件下比现行性能较好的H.264推荐算法平均减少约60%的搜索点数;提出误差曲面参数模型与搜索相结合的分数像素精度快速算法,减少约50%的分数像素精度估计运算量,实现了完整的快速BMA解决方案。本文也给出了实时转码系统的运动重估计方案,满足实际应用需要且复杂度极低。
为了减小运动估计的预测误差,本文从根本上解释了BMA不能表示非平移运动的缺陷,引入基于节点位移的可变形块运动模型,给出预测精度高、运算量低且易于实现的节点位移搜索算法(NS-DBMA),有效减小预测误差。在NS-DBMA基础上,提出了快速计算方法、整数实现方法、双模式混合估计方法、分数像素精度预测方法、六边形搜索方法等改进算法,进一步降低DBMA的实现难度并提高预测精度,整个过程都以整数加法和移位运算实现,适合应用于实际编码系统。测试结果表明,综合各项改进的方法的DBMA的运算量相当于全搜索BMA的16.5%,可将预测图像质量提高3.79dB,在实际编码系统中也可以得到1.2dB的性能提升,具有广泛的应用前景。
Motion estimation and compensation (ME/MC) in video compression is discussed. The block matching algorithm (BMA) produces large prediction error when estimating non-translational motion and it consumes over half computation of video codec. Fast BMA is first discussed and deformable block matching algorithm (DBMA) is proposed to increase the accuracy of prediction.
The human visual system and background knowledge of video coding are introduced to show the guideline of compression and the important role of ME/MC. The popular block-based compression system and existent standards are introduced to show the usage of ME/MC and its history. The common models for video sequences of the real world and some estimation methods are also discussed.
In order to reduce the complexity of BMA, some famous algorithms are summarized first. By analyzing the property of video sequence and real motion field, some key points for speeding up BMA are discussed. Based on those, an adaptive fast search algorithm (APFS) is proposed, which reduces about 60% search points comparing with the algorithms recommend by H.264 while same quality on average. A sub-pixel fast algorithm using both parabolic prediction and search is proposed to reduce half computation of sub-pixel BMA. We also propose a simple motion re-estimation method for video transcoder, which has very low computation and qualifies for real-time transcoding.
For increasing prediction accuracy, BMA is first demonstrated to be inaccurate for nontranslation motion. A nodal-displacement based deformable model is proposed and a nodal search algorithm (NS-DBMA) is developed, which has high prediction accuracy, low computation and is easy to implement. Some improved algorithms, such as fast integer method, two-mode hybrid method, sub-pixel accuracy prediction and hexagon search method, are further proposed. Experimental results show that the improved DBMA has only 16.5% computation of Full Search BMA while outperforms 3.79dB, and also 1.2dB gain in real coding system.
本文介绍了人眼视觉系统生理特性和视频压缩编码的理论基础,指出视频压缩的基本方法和运动估计与补偿的关键作用;介绍了视频压缩编码的系统结构,总结并比较现有的各种视频压缩编码标准,说明运动估计在实际编码系统中的使用方法及发展过程;分析真实场景的运动变化在二维图像上的参数表示方法,并概括介绍各种运动估计方法。
为了降低现行系统中使用的BMA的复杂度,本文首先介绍几种有代表性的快速算法,全面总结了视频信号属性和运动场的分布特征,详细分析利用信号特征加快BMA的方法,在理论分析基础上提出自适应快速搜索算法(APFS),在相近预测质量的条件下比现行性能较好的H.264推荐算法平均减少约60%的搜索点数;提出误差曲面参数模型与搜索相结合的分数像素精度快速算法,减少约50%的分数像素精度估计运算量,实现了完整的快速BMA解决方案。本文也给出了实时转码系统的运动重估计方案,满足实际应用需要且复杂度极低。
为了减小运动估计的预测误差,本文从根本上解释了BMA不能表示非平移运动的缺陷,引入基于节点位移的可变形块运动模型,给出预测精度高、运算量低且易于实现的节点位移搜索算法(NS-DBMA),有效减小预测误差。在NS-DBMA基础上,提出了快速计算方法、整数实现方法、双模式混合估计方法、分数像素精度预测方法、六边形搜索方法等改进算法,进一步降低DBMA的实现难度并提高预测精度,整个过程都以整数加法和移位运算实现,适合应用于实际编码系统。测试结果表明,综合各项改进的方法的DBMA的运算量相当于全搜索BMA的16.5%,可将预测图像质量提高3.79dB,在实际编码系统中也可以得到1.2dB的性能提升,具有广泛的应用前景。
Motion estimation and compensation (ME/MC) in video compression is discussed. The block matching algorithm (BMA) produces large prediction error when estimating non-translational motion and it consumes over half computation of video codec. Fast BMA is first discussed and deformable block matching algorithm (DBMA) is proposed to increase the accuracy of prediction.
The human visual system and background knowledge of video coding are introduced to show the guideline of compression and the important role of ME/MC. The popular block-based compression system and existent standards are introduced to show the usage of ME/MC and its history. The common models for video sequences of the real world and some estimation methods are also discussed.
In order to reduce the complexity of BMA, some famous algorithms are summarized first. By analyzing the property of video sequence and real motion field, some key points for speeding up BMA are discussed. Based on those, an adaptive fast search algorithm (APFS) is proposed, which reduces about 60% search points comparing with the algorithms recommend by H.264 while same quality on average. A sub-pixel fast algorithm using both parabolic prediction and search is proposed to reduce half computation of sub-pixel BMA. We also propose a simple motion re-estimation method for video transcoder, which has very low computation and qualifies for real-time transcoding.
For increasing prediction accuracy, BMA is first demonstrated to be inaccurate for nontranslation motion. A nodal-displacement based deformable model is proposed and a nodal search algorithm (NS-DBMA) is developed, which has high prediction accuracy, low computation and is easy to implement. Some improved algorithms, such as fast integer method, two-mode hybrid method, sub-pixel accuracy prediction and hexagon search method, are further proposed. Experimental results show that the improved DBMA has only 16.5% computation of Full Search BMA while outperforms 3.79dB, and also 1.2dB gain in real coding system.
引文
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