New H.264/AVC Multiple Reference Prediction Algorithm

在H.264/AVC视频压缩标准采用的几项关键技术中,使用多参考帧预测可以增加最佳匹配块的检索概率,进而大大提高了编码效率.受B帧直接( direct)预测模式的启发,提出了一种新的基于扩展帧的多参考帧预测方法,由多参考帧中的共同位置块及其参考块扩展得到一个新的抽取帧,增加了原始序列的时域分辨率,使得扩展帧更加接近当前帧,提高了运动估计中最佳匹配的检索概率,进而提升了编码效率.仿真结果证实该方法的编码性能好于H.264/AVC参考软件.     

视频编码标准H．264的运动补偿技术分析

H.264/AVC建议是目前最新的视频压缩标准.本文分析研究了H.264建议中运动估计的关键技术,包括可变块大小、多帧和亚像素运动估计,并对多参考帧模式下进行多种测试序列的测试,并得出结论.     

一种新型H.264/AVC多参考帧预测方法

在H.264/AVC视频压缩标准采用的几项关键技术中,使用多参考帧预测可以增加最佳匹配块的检索概率,进而大大提高了编码效率。受B帧直接(direct)预测模式的启发,提出了一种新的基于扩展帧的多参考帧预测方法,由多参考帧中的共同位置块及其参考块扩展得到一个新的抽取帧,增加了原始序列的时域分辨率,使得扩展帧更加接近当前帧,提高了运动估计中最佳匹配的检索概率,进而提升了编码效率。仿真结果证实该方法的编码性能好于H.264/AVC参考软件。     

基于UMHexagonS的快速运动估计编码算法研究

成就最新视频编码标准H.264/AVC优异编码性能的代价是其计算复杂度的大幅增加,编码速度的急剧下降.为了克服H.264/AVC标准中重要且耗时的运动估计编码技术实时性差的缺陷,针对其最新采用的UMHexagonS算法的计算冗余,利用宏块的运动特征,制定了自适应的运动估计策略和搜索点分配准则.仿真实验结果表明,本文提出的运动估计编码方案与UMHexagonS算法相比,平均节省约23%的运动估计编码时间,在有效提高编码速度的前提下,保持了H.264/AVC低码率、高质量的编码优势.     

搜索模式自适应快速运动估计算法

提出了一种搜索模式自适应快速运动估计算法(PAFME),首先利用变块尺寸运动估计的特点与运动矢量的时空域相关性,预测初始搜索中心;采用多种搜索模式以适应不同运动特征,提出了搜索模式自适应的选择机制,以节省不必要的搜索点加快搜索速度;又能避免陷入局部极小.实验结果表明,与H.264/AVC的参考软件JM12.4相比,该算法使整像素精度运动估计的速度提高了30%～40%,同时保持了图像质量和码率基本不变.     

基于矢量预测的快速运动估计搜索算法

基于H.264视频编码标准的编解码过程中,运动估计的时间大概要占总编码时间的70%(1个参考帧)到90%(5个参考帧)。对于H.264标准的新特点,传统的全搜索算法的精度高,但计算量太大,不能应用于实时处理;经典的菱形等算法搜索模式简单,易于实现,但容易陷入局部无穷小。采用了一种基于运动矢量预测的快速运动估计搜索算法。该方法首先利用运动矢量的时、空间相关性得到预测矢量,然后利用非对称十字型搜索确定运动估计的起始点,最后采用经典的菱形算法进行运动估计。实验结果表明,相比UMHexagonS快速搜索算法,该算法能够在码率增加不超过1%,信噪比下降不超过0.1 dB的情况下,运动估计速度有较大提高。     

H.264视频编码系统中多参考帧的选择算法研究

H.264/MPEG-4 AVC中引入多参考帧运动补偿来提高视频编码性能,由此产生的多参考帧运动估计(MRF-ME)却带来了巨大的运算代价.本文提出一种基于快速分层特征匹配的运动估计策略(HFM-ME)来加速多参考帧的匹配过程.HFM-ME策略通过引入一种符号截断特征(STF)将块匹配被分解为均值匹配和二进制相位匹配.实验结果表明,与传统的块匹配ME相比,HFM-ME在保持匹配性能的同时显著提高了运算速度.     

一种基于H.264的快速多参考帧选择算法

H．264采用的多参考帧运动估计极大地增加了编码器的复杂度。文中分析了各参考帧在运动估计中的作用,提出一种快速多参考帧选择算法以降低运算复杂度。该算法利用已编码相邻块参考帧的相关性,对参考帧进行预选择和排序,以避免不必要的运动搜索。可以与其它多参考帧运动估计算法相结合。实验结果表明,与H．264参考软件JM9．6中的快速算法UMHexagonS相比,提出的算法在保持编码图像质量的同时,可以进一步降低多参考帧运动估计的运算量,能够节省约35％的编码时间。     

基于H.264的快速运动估计技术

H.264/AVC视频压缩编码标准采用了基于运动补偿的帧间预测编码,用于去除帧间时域冗余。其中运动估计是帧间预测的核心部分,也是最耗时的部分,因此一个高效的运动估计算法能大大提高编码效率。本文重点介绍了H.264/AVC中的快速运动估计UM HexagonS以及与此相结合的CBFPS亚像素运动估计和提前终止技术。     

基于空域特征的H.264快速多参考帧选择算法

提出了一种H.264快速多参考帧选择算法,它利用视频序列的空间相关特性,在运动估计之前判断当前宏块的Skip编码模式,实现在运动估计过程中快速选择编码模式,基于对Skip编码模式占用概率的统计分析,设置多模式下参考帧数量.实验结果表明,本算法在PSNR损耗与全搜索算法相比不超过0.07dB的情况下,平均节约72.5%的编码时间.     

改进的空间下采样视频转码快速运动估计算法

提出一种基于输入码流信息和已转码码流信息的视频转码快速运动估计算法。本算法利用Alpha-激励均值滤波通过输入码流的运动矢量合成作为备选预测运动矢量之一,并利用H．264标准中帧间预测的方法通过已转码码流信息合成另一个备选预测运动矢量,共同作为EPZS运动估计算法的预测中心。结合图像的运动活跃性．自适应的调整运动估计的搜索策略。该算法比传统的运动矢量方法相比提高了1dB左右的PSNR,保持了较高的转码图像质量并与菱形搜索算法相比能够降低18％左右的转码时间。     

An efficient computation-constrained block-based motion estimationalgorithm for low bit rate video coding

We present an efficient computation constrained block-based motion vector estimation algorithm for low bit rate video coding that yields good tradeoffs between motion estimation distortion and number of computations. A reliable predictor determines the search origin, localizing the search process. An efficient search pattern exploits structural constraints within the motion field. A flexible cost measure used to terminate the search allows simultaneous control of the motion estimation distortion and the computational cost. Experimental results demonstrate the viability of the proposed algorithm in low bit rate video coding applications. The resulting low bit rate video encoder yields essentially the same levels of rate-distortion performance and subjective quality achieved by the UBC H.263+ video coding reference software. However, the proposed motion estimation algorithm provides substantially higher encoding speed as well as graceful computational degradation capabilities.     

一种基于子搜索格雷码核的快速视频块运动估计算法

快速视频块运动估计是视频编码中的一个重要问题。在格雷码核( GCK)算法的基础上,提出一种改进的子搜索格雷码核( Sub-GCK)算法。理论上的计算复杂度分析表明：提出的子搜索格雷码核算法的运算量大约为原始格雷码核算法的22.1%。实验比较了子搜索格雷码核算法、原始格雷码核算法和其他几种常见的运动估计算法的编码性能,结果显示：新算法在保证编码质量的前提下,有效降低了运动估计时间,时间约为原始格雷码核算法的41.9%。     

一种基于MPEG-2的立体视频编码中的视差匹配快速算法

高效，快速的视差匹配是立体视频处理中的一项关键技术。本文在分析立体图像序列的视差矢量与运动矢量之间的相关性的基础上，提出一种基于MPEG-2的立体视频编码中的视差匹配快速算法。实验结果表明，与全搜索法相比，在保证重建图像质量的前提下，快速算法能显著降低视差估计的计算复杂度。     

A variable block size motion estimation algorithm for real-time H.264 video encoding

This paper presents an efficient variable block size motion estimation algorithm for use in real-time H.264 video encoder implementation. In this recursive motion estimation algorithm, results of variable block size modes and motion vectors previously obtained for neighboring macroblocks are used in determining the best mode and motion vectors for encoding the current macroblock. Considering only a limited number of well chosen candidates helps reduce the computational complexity drastically. An additional fine search stage to refine the initially selected motion vector enhances the motion estimator accuracy and SNR performance to a value close to that of full search algorithm. The proposed methods result in over 80% reduction in the encoding time over full search reference implementation and around 55% improvement in the encoding time over the fast motion estimation algorithm (FME) of the reference implementation. The average SNR and compression performance do not show significant difference from the reference implementation. Results based on a number of video sequences are presented to demonstrate the advantage of using the proposed motion estimation technique.     

Content-Aware Fast Motion Estimation Algorithm

In this paper, we propose the Content-Aware Fast Motion Estimation Algorithm (CAFME) that can reduce computation complexity of motion estimation (ME) in H.264/AVC while maintaining almost the same coding efficiency. Motion estimation can be divided into two phases: searching phase and matching phase. In searching phase, we propose the Simple Dynamic Search Range Algorithm (SDSR) based on video characteristics to reduce the number of search points (SP). In matching phase, we integrate the Successive Elimination Algorithm (SEA) and the integral frame to develop a new SEA for H.264/AVC video compression standard, called Successive Elimination Algorithm with Integral Frame (SEAIF). Besides, we also propose the Early Termination Algorithm (ETA) to early terminate the motion estimation of current block.We implement the proposed algorithm in the reference software JM9.4 of H.264/AVC and the experimental results show that our proposed algorithm can reduce the number of search points about 93.1%, encoding time about 42%, while maintaining almost the same bitrate and PSNR.     

Fast multi-frame motion estimation for H264/AVC system

Advanced video compression standard, H264/AVC, with multi-frame motion estimation, can offer better motion-compensation than the previous coding standards. However, the implementation of real-time multi-frame estimation for an H264/AVC system is difficult due to heavy computations. In this paper, a fast algorithm is proposed in an effort to reduce the searching computation for motion estimation with five reference frames. The fast multi-frame motion estimation consists of the adaptive full-search, three-step search, and diamond search methods using the content adaptive control process. Efficient control flow is proposed to select the searching algorithm dependent on video features. The adaptive algorithm can achieve better rate-distortion and lower computation for H264/AVC coding. The experiments indicate that the speed-up is 6–15 times compared with the full search method, while the image quality slightly degrades.     

基于边界约束的样品视频非对称运动估计方法

针对常规运动估计方法应用到样品视频编码时存在无效搜索点冗余搜索、有效搜索点遗漏的问题,提出基于边界约束的非对称运动估计方法。首先,在原有预定搜索范围的基础上,采用定点统计运动参量的方法对科学仪器的样品视频运动性能进行测试统计,根据统计结果,对视频运动范围设定边界,减少运动搜索点数;然后提出了基于边界约束的非对称搜索模型,依据样品视频的运动特征,优化搜索算法。来自电子探针和电子显微镜的不同样品视频编码实验表明,与多方向搜索算法(MDS)比较,所提方法的运动估计时间缩短了约33%,编码性能保持甚至超过了多方向搜索算法。     

Level-set-based motion estimation algorithm for multiple reference frame motion estimation

Motion estimation (ME) has a variety of applications in image processing, pattern recognition, target tracking, and video compression. In modern video compression standards such as H.264/AVC and HEVC, multiple reference frame ME (MRFME) is adopted to reduce the temporal redundancy between successive frames in a video sequence. In MRFME, the motion search process is conducted using additional reference frames, thereby obtaining better prediction signal as compared to single reference frame ME (SRFME). However, its high computational complexity makes it difficult to be utilized in real-world applications. In order to reduce the computational complexity of MRFME, this paper proposes a level-set-based ME algorithm (LSME) without any penalty in the rate-distortion (RD) performance. First, the proposed algorithm partitions the motion search space into multiple level sets based on a rate constraint. The proposed algorithm then controls the ME process on the basis of the predetermined level sets. Experimental results show that the proposed algorithm reduces the ME time by up to 83.46% as compared to the conventional full search (FS) algorithm.     

Small-diamond-based search algorithm for fast block motion estimation

A good fast motion search algorithm should efficiently speed up the encoding time and keep the quality of encoded video stable at the same time. Researches have shown that many fast algorithms lose the quality requirement in some special video sequences. These video sequences often have heavy motions and need large search windows for motion vector search. E3SS, DS, and E-HEXBS, which are famous algorithms, are not good enough in these sequences. As to UMHexagonS, it is able to meet the high video quality requirement very well, but it costs too much computation. This paper introduces a multi-stage motion estimation algorithm. The algorithm ensures getting good video quality while decreases the motion search time efficiently. It divides the search regions into many un-overlapped small-diamond regions and forces the motion search to go outward for larger motion vectors. This method is also designed to avoid mistaking local optimal motion vectors. For this reason, the selected motion vector is refined by several stages. Experimental results show that the proposed algorithm uses almost the same number of checking points as E3SS but achieves a better quality. Furthermore, the proposed algorithm is also tested in H.264/AVC JM9.5 encoder; the experimental results show that this algorithm is also suitable for variable block-size motion estimation.