H.264中高效块匹配运动估计方法研究

为降低在视频编码标准H.264中运动估计的高计算复杂度问题,通过对H.264运动估计算法的深入研究,提出了一种利用时空域运动相关性的高效块匹配搜索算法。该算法充分利用视频序列的运动程度与宏块编码模式间的关联特性以及运动矢量的统计特征进行运动模式判定,实现了一种简单高效的块匹配方法,并且根据不同的运动模式动态改变搜索策略。实验结果表明,在保持PSNR方面性能不受损失的同时,减少了运动估计的搜索复杂度,降低了运算复杂度,提高了编码的实时性。     

一种基于H.264的可变块快速运动估计算法

H.264是最新的视频编码标准,它相对于以前的视频编码标准在编码效率上有了巨大的提高。高编码效率得益于采用了一系列新的编码技术,这也导致了较高的计算复杂度。H.264运用了可变块运动估计方法,这也是H.264编码过程中最耗时的模块。提出了一种基于H.264的可变块快速运动估计算法。该算法基于以下3种策略:静止块的预测、非静止块的预测搜索和合并过程中的自适应精细搜索。试验结果证明,该算法能够将计算复杂度降低到快速全搜索运动估计算法的3%,而PSNR和码率几乎与快速全搜索算法得到的结果相当。     

H.264/AVC视频编码技术研究

H.264是最新的视频编码标准.与以往的压缩标准相比,该标准具有更好的压缩性能和网络适应性能.文中分析和研究了H.264编码标准采用的一些新技术,并在此基础上实施了多组实验.实验采用JVT参考软件JM8.6作为测试模型,运用了Mother & Daughter、Foreman和Mobile三个测试序列.实验分别在运动补偿中不同块组合方式、多参考帧、Hadamard变换以及CABAC熵编码等的编码性能几个方面对H.264进行了验证.最后得出了实验结论并在此基础上提出了H.264编码器的优化方向.     

几种基于H.264的运动估计搜索算法的分析

H．264视频编码标准的性能很大程度上取决于运动估计,而影响运动估计的主要是匹配准则和搜索算法。本文对多种匹配准则和快速搜索算法进行了研究,并比较了几种新颖的搜索算法的优缺点,给出了现有的几种搜索算法应用在H．264编码器上的性能比较。     

重用运动矢量和预测残差的MPEG-2/H.264空间分辨率转码

本文提出一种新的MPEG-2到H.264的视频转码算法.它通过充分利用MPEG-2解码过程中得到的运动矢量和宏块编码残差等信息,可显著减少H.264编码过程中宏码编码模式确定和运动估计过程的计算复杂度,并得到最终的H.264视频流.几种典型视频测试序列的仿真实验结果表明,本算法对视频质量的损失较小,有稳定的率失真性能,有利于实时转码的实现.     

EPZS运动估计算法的分析及改进

在分析研究H.264视频编码标准推荐的运动估计核心算法EPZS的基础上,针对该算法运动估计实时性不足的缺点,提出一种对EPZS算法进行起始搜索窗口中心点和计算终止条件判断标准的改进方法,在H.264编码器的参考模型JM10.1中,选择5个测试序列进行实验。实验结果表明,改进后的算法与原算法相比,在重建图像质量和码率接近的情况下,运动估计时间平均节省了29.314%,降低了算法的复杂度,提高了编码的实时性。     

H.264视频码流中运动物体的提取

H.264是新一代视频编码标准,具有广泛的应用前景。本文主要讨论了基于H.264视频流中运动物体检测的问题。首先简要介绍了H.264视频编码标准,然后分析了各种编码图像帧的编码过程,从而得出根据运动矢量来检测运动物体的方法,并分析了因摄像机运动而对检测方法造成的影响及相应的处理方法。从实验结果可以看出,检测效果还是比较令人满意的。     

新视频压缩标准H.264/AVC的研究

H.264/AVC是由ITU T视频编码专家组和ISO/IEC运动图像专家组成立的联合视频专家组制定的最新视频编码标准。H.264/AVC标准的主要目标是增强压缩性能,并提供“网络友好”的视频表达。概述了H.264的特点及应用,并详细介绍了H.264/AVC的核心技术。     

H．264／觚忙视频编码技术研究

H．264是最新的视频编码标准。与以往的压缩标准相比,该标准具有更好的压缩性能和网络适应性能。文中分析和研究了H．264编码标准采用的一些新技术,并在此基础上实施了多组实验。实验采用JVT参考软件JM8．6作为测试模型,运用了Mother＆Daughter、Foreman和Mobile三个测试序列。实验分别在运动补偿中不同块组合方式、多参考帧、Hadamard变换以及CABAC熵编码等的编码性能几个方面对H．264进行了验证。最后得出了实验结论并在此基础上提出了H．264编码器的优化方向。     

一种新的基于H.264/AVC的零块判决方法

在基于运动估计和预测编码的视频编码方案中,有一种简单而有效的快速实现方法——零块判决方法,H．264／AVC使用的也是基于运动估计和预测编码的视频编码方案,所以也可以运用零块判决方法来加快其编码速度．根据H．264／AVC视频编码标准的新特点,对其中的零块判决阈值进行了推导,提出了新的适合于H．264／AVC的零块判决方法,并进行了仿真测试,实验结果表明,在中低码率的视频编码中,该方法在编码效率基本保持不变的条件下,编码时间减少了20％～47％．     

Content-Aware Prediction Algorithm With Inter-View Mode Decision for Multiview Video Coding

3-D video will become one of the most significant video technologies in the next-generation television. Due to the ultra high data bandwidth requirement for 3-D video, effective compression technology becomes an essential part in the infrastructure. Thus multiview video coding (MVC) plays a critical role. However, MVC systems require much more memory bandwidth and computational complexity relative to mono-view video coding systems. Therefore, an efficient prediction scheme is necessary for encoding. In this paper, a new fast prediction algorithm, content-aware prediction algorithm (CAPA) with inter-view mode decision, is proposed. By utilizing disparity estimation (DE) to find corresponding blocks between different views, the coding information, such as rate-distortion cost, coding modes, and motion vectors, can be effectively shared and reused from the coded view channel. Therefore, the computation for motion estimation (ME) in most view channels can be greatly reduced. Experimental results show that compared with the full search block matching algorithm (FSBMA) applied to both ME and DE, the proposed algorithm saves 98.4–99.1% computational complexity of ME in most view channels with negligible quality loss of only 0.03–0.06 dB in PSNR.      

一种复杂度约束下基于宏块优先顺序的运动估计优化算法

在实际应用中,视频编码算法不仅需要提供最好的编码效率,而且还需要自动地适应各种平台不同的计算能力约束.这是一个在复杂度约束下的率失真优化问题.针对视频编码消耗计算资源最多的运动估计过程,提出一种复杂度约束下的优化算法.该算法对运动估计的失真度和复杂度建模,并通过该模型决定每个宏块的预测失真度一复杂度斜率(distortion-complexity slope,DC-slope),以此决定各个宏块运动估计的优先顺序,然后通过一个常微分方程建立控制参数与计算复杂度之间的关系,准确地控制运动估计的计算复杂度.通过实验比较,本算法不仅可以自适应地调整运动估计的计算复杂度,而且能在不同的复杂度约束下提供优化的编码性能.     

面向视频会议的运动估计快速算法

针对H.264/AVC视频压缩算法中运动估计模块计算复杂度高的问题,提出了一种基于积分图像的运动估计快速算法.算法通过对单元块进行预计算求和,在块匹配运算时使用单元块级绝对差值.该算法能够在保证视频编码质量的前提下,大幅度提高运动估计模块的计算效率.算法适用于视频会议等要求视频实时压缩的应用.     

基于宏块内部特征的H.264快速预测模式决策算法*

为了提高视频质量、降低码率,H.264/AVC采用了七种块划分类型,使得在提高编码性能的同时带来了高计算复杂度。研究了宏块的内部特征,提出了一种基于宏块内部信息复杂度的快速帧间模式选择算法。实验数据表明,在保证重建图像信噪比的情况下,该算法降低了帧间预测的复杂度,可平均节省17%24%的编码时间,满足了实时视频通信的要求。     

An efficient multi-layer reference frame motion estimation for video coding

Most of the fast search motion estimation algorithms reduce the computational complexity of motion estimation (ME) greatly by checking only a few search points inside the search area. In this paper, we propose a new algorithm—multi-layer motion estimation (MME) which reduces the computational complexity of each distortion measure instead of reducing the number of search points. The conventional fast search motion estimation algorithms perform ME on the reference frame with full distortion measure; on the contrary, the MME performs ME on the layers with partial distortion measures to enhance the computational speed of ME. A layer is an image which is derived from the reference frame; each macro-pixel value in the layer represents the sum of the values of the corresponding pixels in the reference frame. A hierarchical quad-tree structure is employed in this paper to construct multiple layers from the reference frame. Experimental results on different video sequences show evidence that many motion vectors have been found similar both in the reference frame and the layers. The effectiveness of the proposed MME algorithm is compared with that of some state-of-the-art fast block matching algorithms with respect to speed and motion prediction quality. Experimental results on a wide variety of video sequences show that the proposed algorithm outperforms the other popular conventional fast search motion estimation algorithms computationally while maintaining the motion prediction quality very close to the full-search algorithm. Moreover, the proposed algorithm can achieve a maximum of 97.99 % speed-improvement rate against the fast full-search motion estimation algorithms which are based on hierarchical block matching process. The proposed MME performs the motion estimation on the layers by using three types of search patterns. The derivation of these search patterns exploits the characteristic of the center-biased motion vector distribution and that of less intensive block distortion measurement of the layers.     

Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification

In video coding, research is focused on the development of fast motion estimation (ME) algorithms while keeping the coding distortion as small as possible. It has been observed that the real world video sequences exhibit a wide range of motion content, from uniform to random, therefore if the motion characteristics of video sequences are taken into account before hand, it is possible to develop a robust motion estimation algorithm that is suitable for all kinds of video sequences. This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. In the first step, spatio-temporal correlation has been used for initial search centre prediction. This strategy decreases the effect of unimodal error surface assumption and it also moves the search closer to the global minimum hence increasing the computation speed. Secondly, the homogeneity analysis helps to identify smooth and random motion. Thirdly, global minimum prediction based on unimodal error surface assumption helps to identify the proximity of global minimum. Fourthly, adaptive search pattern selection takes into account various types of motion content by dynamically switching between stationary, center biased and, uniform search patterns. Finally, the early termination of the search process is adaptive and is based on the homogeneity between the neighboring blocks.Extensive simulation results for several video sequences affirm the effectiveness of the proposed algorithm. The self-tuning property enables the algorithm to perform well for several types of benchmark sequences, yielding better video quality and less complexity as compared to other ME algorithms. Implementation of proposed algorithm in JM12.2 of H.264/AVC shows reduction in computational complexity measured in terms of encoding time while maintaining almost same bit rate and PSNR as compared to Full Search algorithm.     

基于分组误差的快速分数像素运动估计算法

H.264是最新一代的视频编码标准,它支持高精度分数像素运动估计。当在整数运动估计中采用快速算法后,分数像素的运动估计可能成为制约快速运动估计算法性能的瓶颈。根据匹配准则的目标函数在最优运动矢量的附近都是单调递增这一假设,提出一种基于分组误差的快速分数像素运动估计算法。实验结果表明该算法不但能够有效降低分数像素运动估计的计算量,而且还能保持较小的率失真性能损失。     

An Efficient Mode Decision Algorithm for H.264/AVC Encoding Optimization

The H.264 video coding standard significantly outperforms previous standards in terms of coding efficiency. However, this comes as a cost of extremely high computational complexity due to mode decision where variable block size motion estimation (ME) is employed. In this paper, we propose an efficient algorithm to jointly optimize mode decision and ME. A theoretical analysis is performed to study the sufficient condition to detect all-zero blocks in H.264, and thus adaptive thresholds are derived to early terminate mode decision and ME. Besides the aforementioned early termination technique, the proposed algorithm also introduces temporal-spatial checking, thresholds based prediction and monotonic error surface based prediction methods to skip checking unnecessary modes. Experimental results demonstrate that the proposed algorithm can significantly reduce the computational complexity of H.264 encoding while maintaining almost the same rate distortion (RD) performance as the original encoder     

一种基于H.264/AVC的高性能快速运动估计算法

为了降低运动估计的计算量,提出一种基于H.264/AVC的快速运动估计算法。该算法使用了提前终止策略和自适应的搜索范围,结合运动矢量预测以及多模板搜索。实验结果表明,在编码性能接近全搜索(fullsearch,FS)算法的同时,本算法比FS和UMHexagonS算法平均节省了65.42%和32.76%的运动估计时间,大幅度提高了编码速度。