基于运动特征的H.264压缩域对象分割

基于从H.264压缩域提取的运动场,提出了一种新的运动对象分割方法.首先采用矢量中值滤波方法滤除运动场中的噪声矢量;再运用后向估计的方法重建预测运动场并进行运动场的累积;然后对存在背景运动的累积运动场进行全局运动补偿;最后基于幅度、散度和旋度3个运动特征,采用改进的统计区域合并方法将运动对象分割出来.实验结果表明.本文方法适用于背景静止或背景运动的H.264压缩视频,且分割质量较好.     

基于粒子群聚类的H.264压缩域运动目标分割

提出了一种基于H.264压缩域的运动目标分割方法.首先从压缩流中提取运动矢量场,采用矢量中值滤波方法滤除运动场的噪声和非真实运动块;再运用前向估计方法进行矢量场的累积,解决了帧内预测时无运动矢量的问题;最后运用基于粒子群聚类算法对运动对象进行自适应分割.试验结果表明,该方法能有效分割出H.264压缩域的运动目标.     

基于H.264压缩域的运动对象快速分割方法

针对H.264压缩域的运动对象分割问题,提出了一种基于Fisher准则的运动对象分割方法。首先将运动对象中每个宏块中子块的运动矢量进行加权,获取每个宏块的运动矢量,然后利用多帧的运动矢量进行累加,获取整个宏块的运动矢量,最后使用Fisher准则将运动对象的矢量分类,从而获取H.264压缩域中的运动对象。通过实验证明,在基本满足运动对象分割准确率的前提下,达到了较好的实时性。     

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。     

基于GA的压缩域中全局运动估计及在字幕遮挡区域恢复中的应用

文章提出了一种直接使用压缩域中的运动矢量进行全局运动估计的方法,并用遗传算法优化输入运动矢量与全局运动参数所产生运动矢量的平均匹配误差.最终的实验结果表明本文的方法能够很好的估计出全局运动的参数.并且提出了一种运用全局/局部运动信息进行视频中字幕遮挡区域的恢复的方法.实验结果表明该方法取得了较好的视觉效果.     

H.264和AVS多模视频解码器中运动矢量预测的硬件实现

文章比较了H.264和AVS两个标准在运动补偿中运动矢量预测算法的差别,提出了一种实现H.264中主档次（main profile）下的第4级别（level 4）和AVS中的基准档次面向高清应用时运动矢量预测复用的硬件结构.提出了一种新颖的缓存管理更新机制,极限情况下用于运动矢量的片上缓存大小减少了75%.用FPGA验证结果表明资源占用情况是单独实现AVS的2.3倍,是单独同时实现两个标准的70%.能实现对1080i 30Hz高清图像实时解码.     

基于运动矢量多级分析的视频全局运动估计

基于运动矢量场的视频全局运动估计相较于基于像素的估计方法具有较低的计算复杂度,因而广泛应用于视频分割及视频压缩等领域中。然而噪声和前景目标等外点区域的存在,降低了全局运动估计的准确性。为了提高全局运动估计的准确度,该文提出一种基于运动矢量多级分析的全局运动估计算法,该算法根据局部运动与全局运动的运动特性差异自适应地滤除前景目标区域,由邻域矢量间相似性度量检测出纹理平滑周期区域,最后滤除孤立的噪声区域,由滤波得到的内点区域求解全局运动参数。实验结果表明,该方法能有效地滤除外点区域,提高全局运动估计的准确性。     

一种快速的半像素运动矢量搜索算法

提出了一种基于梯度预测的快速半像素运动矢量搜索算法.实验结果表明,在H.263编码器中使用该算法的运算量,比在相同量化阶下的半像素运动矢量搜索算法下降45%,并且图像的PSNR和码率变化很小.该算法可以很容易地应用到H.264的1/4像素运动矢量搜索中.     

一种基于H．264的有效运动估计算法

运动估计算法是实时视频编解码技术的研究重点，高精度的匹配和补偿可以减少预测误差，提高视频图像的压缩效果．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，提出了采用一种基于节点模型的可变形块匹配运动估计算法来搜索最佳运动矢量．该算法充分利用了H．264运动矢量的的统计特性和相关性，并采用基于像素差值分类的运动估计匹配准则．实验表明，在编码性能损失很小的条件下，该算法有效降低了视频压缩编码中运动估计的运算复杂度．     

基于H.264压缩域的运动目标检测算法

基于H264压缩域的运动目标检测算法。首先,从压缩码流中提取原始运动矢量场,采用中值滤波法滤除运动场中由噪声引起的运动矢量;再利用从压缩码流中提取的宏块分割类型初步排除一些分块较大的伪运动块;然后采用自适应阈值选取法定位出运动区域;最后,通过已定位的运动区域的特征进一步精确识别出运动目标。算法充分利用了H264码流中的运动矢量信息,简单易于实现,适用于智能监控,视频分析等领域。试验结果表明,该算法检测效果较好,且不需要对压缩码流进行全部解码。     

结合空时域下采样与重建的H.264/AVC压缩性能优化

为提高H.264/AVC标准在带宽资源严重受限时的压缩效率,采用空时域相结合的编码思路,提出了一种基于运动检测的自适应抽帧方法,并结合空域下采样与重建研究了一种改进的H.264/AVC压缩性能优化框架。在编码端,原视频先空域下采样以减少空间分辨率,然后根据视频运动特征,采用不同抽帧模式自适应地降低帧率,再经H.264/AVC编码,有效降低了编码码率。在解码端,解码视频则采用与抽帧模式相对应的运动估计与补偿插帧方法重建出抽取帧,再利用超分辨率重建技术将视频恢复到原空间分辨率。实验结果表明,所提方法在低码率段的视频压缩性能优于H.264/AVC标准编解码及相关文献方法。     

Global motion estimation from randomly selected motion vector groups and GM/LM based applications

Fast global motion estimation has been paid much attention in video compression and analysis. In this paper, a global motion estimation method is proposed by randomly selected motion vector groups in the compression domain directly. It is carried out by refining the centroid of the global motion parameters corresponding to the motion vector groups. Simulation results on different global motions show its effectiveness and robustness against noise and motion vector loss. Finally, two applications, namely the text occluded region recovery and the error concealment, are presented using the global motion/local motion information. Experimental results show the effectiveness of the proposed method. This work is supported in part by China National Natural Science Foundation (CNSF) under Project No.60572045, the Ministry of Education of China Ph. D. Program Foundation under Project No.20050698033, and by a Cooperation Project (2005.7- 2007.7) with Microsoft Research Asia.     

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.     

A novel moving object segmentation framework utilizing camera motion recognition for H.264 compressed videos

This paper presents a novel coarse to fine moving object segmentation framework for H.264/AVC compressed videos. The proposed framework integrates the global motion estimation and global motion compensation steps in the segmentation pipeline unlike previous techniques which did not consider such an integration. The integration is based on testing for presence of global motion by classifying the interframe motion vectors into moving camera class and still camera class. The decision boundary separating these two classes is learnt from the training video data. The integration automates the moving object segmentation to be applicable for static, moving and combination of static/moving camera cases which to the best of our knowledge has not been carried out earlier. Further, a novel coarse segmentation technique is proposed by decomposing the inter-frame motion vectors into wavelet sub-bands and utilizing logical operations on LH, HL and HH sub-band wavelet coefficients. The premise is based on the fact that since the LH, HL and HH sub-bands contain the detail information pertaining to horizontal, vertical and diagonal moving blocks respectively, they can be exploited to identify the coarse moving boundaries. The coarse segmentation is fast in comparison to state-of-the-art coarse segmentation methods as demonstrated by our experiments. Finally, these coarse boundaries are modeled in an energy minimization framework and shown that by minimizing the energy using graph cut optimization the segmentation is refined to obtain the fine segmentation. The proposed framework is tested on a number of standard video sequences encoded with H.264/AVC JM encoder and comparison is carried out with state-of-the-art compressed domain moving object segmentation methods as well as with an existing state-of-the-art pixel domain method to establish and validate the proposed moving object segmentation framework.     

基于H.264编码的多屏共享系统研究

H.264/AVC是一种由ITU-T视频编码专家组合ISO/IEC JTC1动态图像专家组联合提出的高度压缩视频编码器标准。然而H.264/AVC编码器较高的运算复杂度提高了多屏共享系统的延迟时间。H.264/AVC由多种开源的实现,其中X264因简单高效而得到广泛的应用。在此对多频共享系统的关键技术进行实现,分析X264编码器提供的运动估计算法并且提出一种优化的算法。实验表明,新的算法提高了编码的速度、减少了系统延迟时间,同时视频质量几乎没有产生损失。     

A low-power oriented architecture for H.264 variable block size motion estimation based on a resource sharing scheme

In the Advanced Video Coding (AVC) standard, motion estimation (ME) adopts many new features to increase the coding performances such as block matching algorithm (BMA), motion vector prediction (MVP) and variable block size motion estimation (VBSME). However, VBSME is utilized in the MPEG4-AVC/H.264 standard which leads to high computational complexity and data dependency that make the hardware implementation very complex.     

基于拟合平面插值的时域错误隐藏算法研究

针对H.264/AVC压缩视频码流在无线信道传输过程中由于运动矢量失配导致图像重构质量下降的问题,本文提出了一种基于拟合平面插值的时域错误隐藏算法。该算法主要利用平面拟合算法对受损宏块运动矢量进行重建,同时采用外边界匹配算法选取最优运动矢量对受损图像进行恢复重建。实验表明,该算法不仅避免了原始算法产生的方块效应,而且在不同的RTP丢包概率下,该算法提升了峰值信噪比,恢复重建的图像质量在主观方面和客观方面都有很大的改善。     

Joint depth-motion dense estimation for multiview video coding

The multiview video coding (MVC) extension of H.264/MPEG-4 AVC [1] is one of the most promising visual encoders for three-dimensional television and free viewpoint video applications. In this paper, we propose a joint dense motion/disparity estimation algorithm, designed to replace the classical temporal/inter-view unit within MVC, which uses a block-based motion/disparity estimation. The motion vector fields and the disparity vector fields are therefore simultaneously derived using the stereo-motion consistency constraint in a set theoretic convex optimization framework. The obtained displacement vector fields are then jointly segmented by minimizing a rate-distortion cost function, in line with the multiple reference frame strategy used in H.264/MPEG-4 AVC. Experimental results demonstrate the benefits of the proposed method compared to the separated dense estimation scheme or the block-based estimation technique.     

一种基于ρ域的H．264／AV码率控制算法

提出了一种基于ρ域线性率失真模型的H．264／AVC码率控制方法。算法主要利用ρ域线性率失真模型来解决量化参数同时用于码率控制和率失真优化的矛盾。同时,用非零运动向量个数来估计宏块的头比特数,进而解决头比特的合理估计问题。实验通过对新算法和JVT—H017算法的比较,得到本文算法不但可以获得更精确的码率控制,而且使输出码率更加的平稳,本文算法实现相对简单,适用于实时视频通信。