H.266合并模式候选决策的研究与改进

针对H.266中基于历史块的运动矢量预测（HMVP）技术在换行更新列表过程中无法参考之前运动信息,以及HMVP候选列表在加入Merge列表过程中存在繁琐的去冗余过程的问题,提出一种改进的H.266合并模式候选决策算法。通过临时存储一个HMVP候选列表来解决原有HMVP列表在换行清空时存在的无法参考之前运动信息的不足,从而更好地预测运动信息。通过Merge候选列表中原有的空时域候选数量来确定需要进行去冗余的HMVP候选数量,以简化去冗余过程。实验结果表明,与H.266标准算法相比,该算法在随机接入的配置下,测试图像序列的亮度分量能够平均节省0.46%的码率,编码总时间平均缩短4.09%,帧间预测时间平均缩短10.87%,能够提高编码性能同时降低编码复杂度。     

一种利用预测运动矢量改进的H.264快速运动估计算法

针对H.264标准推荐使用的快速运动估计算法——非对称十字型多层次六边形格点搜索（Unsymmetrical cross multi-hexagon grid search, UMHexagonS）算法搜索速度慢的问题,提出了一种改进算法。在起始搜索点的预测环节,建立预测矢量集,并根据预测矢量集的长度信息决定后续的搜索策略;在全局搜索环节,利用预测运动矢量之间的相关性适当跳过某些搜索步骤,并更换一些搜索模板;并且,根据整数变换和量化的特性检测全零系数块,提前终止运动估计过程。实验结果表明,在量化步长为28时,本文算法比UMHexagonS算法平均减少了34.80%的运动估计时间,同时编码性能基本不变。该算法在不同量化步长的条件下能够适应不同运动强度的视频序列,是一种适合H.264的速度快且性能好的快速运动估计算法。     

H.264运动估计UMHexagonS算法的优化与改进

针对H.264中UMHexagonS算法存在的不足,提出了一种改进的快速运动估计算法。改进算法根据起始预测运动矢量成为最佳点的可能性大小对起始预测运动矢量的检测顺序进行了优化,提高了编码效率;设计了一种改进的5×5螺旋全搜索模板,减少了5×5螺旋全搜索模板的搜索点数;增加了一种针对亚宏块的提前终止策略,进一步减少了运动估计带来的运算量。实验结果表明,改进算法在基本保持UMHexagonS算法编码性能的同时,有效减少了运动估计时间,提高了编码效率,并且可适用于不同运动强度的视频序列。     

基于UMHexagonS的运动估计算法优化

针对UMHexagonS算法冗余搜索的问题,使用大十字搜索判定结果,改进原有的运动估计算法。改进算法判断最优点可能分布区域,使用相应改进搜索模板搜索,降低搜索点个数,达到避免冗余搜索的目的,提高运动估计搜索效率。在多组视频序列中测试,图像质量相近情况下,改进算法比UMHexagonS算法有了显著的提高。特别是在剧烈运动的视频序列中,改进算法比UMHexagonS算法的运动估计时间减少了45.78%,编码耗时缩短了34.97%,比EPZS算法运动估计时间减少了35.25%,编码耗时缩短了25.45%。     

一种基于宽钻石搜索的改进TZS算法

针对高效视频编码中运动估计的计算复杂度高和消耗大量编码时间的问题,提出一种改进的TZS算法,从而有效提升视频编码效率.首先对搜索区域进行运动矢量预测,确定起始搜索点;再使用宽钻石搜索算法代替钻石搜索算法来搜索率失真最小点;然后根据运动矢量的十字中心偏置的分布特点,采用八边形-十字栅格模式进行栅格搜索,减少编码过程中的搜...     

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帧间编码可变块阈值选择算法

为有效预测运动矢量,降低运动估计复杂度,提出一种阈值选择算法。设定阈值以确定当前块是否为预测运动矢量块,对最佳运动矢量块做出判定,以提前终止运动估计。在JM10.2平台上与UMHexagonS算法进行对比测试,验证该算法的性能。实验结果表明,该算法缩短了约84%的编码时间,提高了编码效率,而视频质量无明显下降,满足实时应用的需求。     

面向立体视频的视差-运动同步联立预测算法

针对立体视频序列的时间空间冗余和交叉冗余,提出一种快速编码算法.应用立体-运动约束模型在视差域和运动域进行联合迭代搜索,根据每次迭代后的模型误差设置自适应修正窗口来保证预测矢量精度,视差矢量和运动矢量可以快速同步获得.实验结果表明,该算法在保证高率失真性能的同时,可以大幅度降低编码复杂度.     

新的多八边形快速运动估计算法

由于对编码的高精度和低复杂度的要求,H.264视频编码标准已经采用了UMHexagonS算法作为其可行的块运动估计实施方案。提出了一种新的UMHexagonS改进算法,改进主要在三个方面：第一,增加了一个新的初始预测矢量,以避免过早陷入局部最优;第二,一个小八边形搜索和两个后续的小菱形搜索取代了UMHexagonS算法中的5×5全搜索,这在一定程度上减少了计算量;第三,多八边形格点搜索取代了多六边形格点搜索,这不仅减轻了运算量负担,也在方向上能更好更快地搜索到最佳运动矢量。实验结果表明,所提出的方法不仅能保证UMHexagonS算法的编码效果,同时还能减少5%~10%的运算量,从而节省编码时间。     

一种基于块匹配的自适应快速运动估计算法

块匹配运动估计算法是实时视频编解码技术的研究重点.为降低视频编码中运动估计的计算复杂度,考虑到现实序列运动矢量的分布存在方向性,文章提出了基于块匹配的自适应快速运动估计算法.该算法在运动估计的初始阶段,利用相邻宏块间的空间相关性来预测初始搜索点的位置,使搜索起点更接近理想的最优匹配点;在搜索过程中引入具有方向特征的非对称十字形搜索模型,加快了搜索速度.实验结果表明该算法具有很好的性能.     

H.264/AVC中基于决策树的P帧快速模式选择（HHME2013第61号论文）

目的：H.264/AVC帧间预测编码需要对所有可能编码模式计算并比较率失真代价,众多的模式类型导致了P帧编码的计算复杂度非常高。本文提出了一种针对P帧的基于决策树的快速选择候选模式算法。方法：在对宏块进行16×16的帧间运动估计后,首先根据残差宏块中4×4全零系数块个数对部分宏块直接选择出候选模式;然后使用16个4×4块的SATD值,采用决策树分类方法对其余宏块选择候选模式。结果：由于只需对候选模式进行编码,因此有效降低了编码器的计算复杂度。实验结果表明,与原始全搜索编码算法相比,该算法对不同运动程度的视频序列获得了较一致的编码时间节省,同时平均峰值信噪比的损失和平均比特率的增加均较少。结论：本文提出了一种新的P帧帧间预测候选模式选择算法,根据帧间运动估计后的残差宏块信息,采用决策树方法对候选模式集进行分类。实验结果表明,该算法能在保证视频编码质量的前提下,有效地降低编码过程中的计算量,缩短编码时间。     

Motion and disparity vectors early determination for texture video in 3D-HEVC

3D-HEVC is the state-of-the-art video coding standard for 3D video, and it is an extension of high efficiency video coding (HEVC) standard. Besides the original HEVC coding tools, 3D-HEVC adopts some advanced coding tools, such as disparity vector (DV), inter-view prediction and inter-component prediction. However, these advanced tools lead to extremely high encoding complexity at the same time, thus it cannot be well applied in real-time multimedia systems. In this paper, we propose a motion and disparity vectors early determination algorithm to reduce 3D-HEVC computational complexity. First, based on the statistical analyses, the spatial and temporal motion vector (MV) candidates are adaptively reduced for the prediction unit (PU) with the Merge mode. Then, for the PU with the Inter mode, the combination of spatial and temporal candidates is used to early determine the final MV. Finally, an adaptive optimization algorithm is adopted to select the valid inter-view disparity vectors (DV) candidates. Moreover, if the difference between candidate vectors is within a conditional range, current PU will be encoded with the Merge mode to skip unnecessary coding process. Experimental results show that for the texture views encoding, the proposed algorithm achieves an average of 33.03% encoding time saving, and an average of 0.47% BD-Rate increases.

     

H.264/AVC中基于决策树的P帧快速模式选择

目的 H.264/AVC帧间预测编码需要对所有可能编码模式计算并比较率失真代价,众多的模式类型导致了P帧编码的计算复杂度非常高。为此提出一种针对P帧的基于决策树的快速候选模式选择算法。方法在对宏块进行16×16的帧间运动估计后,首先根据残差宏块中4×4全零系数块个数对部分宏块直接选择出候选模式;然后使用16个4×4块的变换域系数绝对值之和(SATD)值,采用决策树分类方法对其余宏块选择候选模式。结果由于只需对候选模式进行编码,因此有效降低了编码器的计算复杂度。实验结果表明,与原始全搜索编码算法相比,该算法对不同运动程度的视频序列获得了较一致的编码时间的节省,同时平均峰值信噪比的损失和平均比特率的增加均较少。结论新的P帧帧间预测候选模式选择算法,根据帧间运动估计后的残差宏块信息,采用决策树方法对候选模式集进行分类。实验结果表明,该算法能在保证视频编码质量的前提下,有效地降低编码过程中的计算量,缩短编码时间。     

Fast multiframe motion estimation algorithms by motion vector composition for the MPEG-4/AVC/H.264 standard

The MPEG-4/AVC/H.264 video coding standard adopts various coding schemes such as multiple reference frames and variable block sizes for motion estimation. Hence, MPEG-4/AVC/H.264 provides gains in compression efficiency of up to 50% over a wide range of bit rates and video resolutions compared to previous standards. However, these features result in a considerable increase in encoder complexity, mainly regarding to mode decision and motion estimation. The proposed algorithms use the stored motion vectors to compose the motion vector without performing the full search in each reference frame. Therefore, the proposed algorithms can obtain an average speed up ratio of four for encoding, thus benefiting from the prediction of the motion vector for the reference frames in advance and maintaining good performance. Any fast search algorithm can be utilized to further largely reduce the computational load.     

一种基于H.264的快速运动估计算法

H.264标准采用了新的编码模式,使H.264的编码压缩效率比先前的标准提高了50%以上,但这些新的编码模式也增加编码器的复杂度和编码运算时间.一种基于H.264的全方向十字型快速运动估计搜索算法,能够在视频质量最少损失的情况下,显著提高运动估计的搜索速度,降低编码器的设计复杂度并可以节省编码时间.     

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.     

Fast motion and disparity estimation for multiview video coding

Multiview video involves a huge amount of data, and as such, efficiently encoding each view is a critical issue for its wider application. In this paper, a fast motion and disparity estimation algorithm is proposed, utilizing the close correlation between temporal and interview reference frames. First, a reliable predictor is found according to the correlation of motion and disparity vectors. Second, an iterative search process is carried out to find the optimal motion and disparity vectors. The proposed algorithm makes use of the prediction vector obtained in the previous motion estimation for the next disparity estimation and achieves both optimal motion and disparity vectors jointly. Experimental results demonstrate that the proposed algorithm can successfully save an average of 86% of computational time with a negligible quality drop when compared to the joint multiview video model (JMVM) full search algorithm. Furthermore, in comparison with the conventional simulcast coding, the proposed algorithm enhances the video quality and also greatly increases coding speed.     

Fast motion and disparity estimation for multiview video coding

Multiview video involves a huge amount of data, and as such, efficiently encoding each view is a critical issue for its wider application. In this paper, a fast motion and disparity estimation algorithm is proposed, utilizing the close correlation between temporal and inter-view reference frames. First, a reliable predictor is found according to the correlation of motion and disparity vectors. Second, an iterative search process is carried out to find the optimal motion and disparity vectors. The proposed algorithm makes use of the prediction vector obtained in the previous motion estimation for the next disparity estimation and achieves both optimal motion and disparity vectors jointly. Experimental results demonstrate that the proposed algorithm can successfully save an average of 86% of computational time with a negligible quality drop when compared to the joint multiview video model (JMVM) full search algorithm. Furthermore, in comparison with the conventional simulcast coding, the proposed algorithm enhances the video quality and also greatly increases coding speed.