基于矢量相关性的自适应运动估计搜索算法

为了减少运动估计的计算量,提高视频压缩编码的效率,提出了一种基于矢量相关性的自适应运动估计搜索算法(简称NAME算法),该算法通过判断当前所要编码块的左、上、右上3个相邻块所对应的运动矢量之间的相关性,将所要编码的块划分为相关类型块和独立类型块,并自适应地对相关类型块和独立类型块采用不同的搜索方式以减少搜索点数并保证搜索准确度。仿真结果表明,该算法与全搜索、菱形搜索和六边形搜索等快速算法相比,在保证图像质量的前提下,搜索速度有了明显的提高。     

基于滤波的运动向量的快速估计算法

基于块匹配的运动向量的估计算法被多种国际视频编码标准所采用,其计算复杂度一直是一个研究的热点。为了提高运动向量估计算法的速度和精度,从运动向量的均匀性出发,提出了一种由宏块分类、运动向量滤波和高效搜索中止准则等策略构成的运动向量场自适应搜索算法,从而实现了块运动向量快速而有效地估计。实验表明,本算法搜索速度接近N3SS和N4SS,而搜索效果方面优于MPEG-4最新推荐的快速运动估计算法PMVFAST和MVFAST。     

H.264块运动估计自适应快速搜索算法研究

H.264视频编解码标准中由于运动搜索部分占整个编码时间的权重很大,所以运动搜索算法的优劣直接影响整个编码的效率。对编码运动估计理论进行了研究,采用六边形和小菱形相结合的方法,提出了一种新的自适应快速搜索算法来改善搜索效率。自适应快速搜索算法模式由当前块运动强度来决定,当当前块处于剧烈运动时,该算法选择六边形图形搜索算法;当当前块处于缓慢运动时,该算法选择小菱形图形搜索算法。实验结果表明该算法相比其他自适应算法以及单纯使用一种搜索图形节约了搜索时间,同时率失真性能影响甚微。     

自适应选择编码模式的快速运动估计算法

针对目前运动估计算法中分割块选择与阈值造成的算法搜索冗余现象,提出一种自适应选择编码模式的快速运动估计算法。在阈值的选取上通过提出自适应的阈值选取方式,来提高算法的搜索精度。而在模块的选取上,则是通过结合视频图像的空间相关性与运动特性来对其进行择优,并采用几种搜索模板来对分割块进行搜索,进而降低运动估计模块的计算复杂度。实验结果表明,该算法能够在得到与全搜索算法相近重构图像质量的情况下减少97%的运算时间。     

Optimization of Motion Estimation Algorithm Based on FPGA Hardware System and Video Tracking

Motion Estimation (ME) is a computationally expensive step in video tracking. A thorough search technique produces the best execution time and the best accuracy. Computational burden, many fast search algorithms limit and report the number of places to search. Motion estimation, analysis of image sequences, computer vision, tracking a target, and is a critical process in a wide range of fields and applications such as video coding. Precision motion estimation lowers significantly bit rate, but can require a complexity of higher computational. This is different reference frames, sub-pixel estimation, and video compression standards, including techniques such as variable block size, MPEG, especially true for a new generation. Only the motion estimation in H.261 is limited to an integer pixel accuracy, rather than the pixel grid, not in the object is often located, move to move between pixels. The system proposed in the motion vector optimization motion estimation (OME) pixel accuracy. By estimating the amount of displacement at a finer resolution, improve prediction, it can expect better performance than motion estimation using an integer pixel precision. Optimization motion estimation (OME) and the compensation method is very similar to that employed in other standards. The main is that block-based motion estimation and compensation is suitable for optimization structures in MPEG-4. Motion estimation (ME) is one of the most computationally-intensive companies in the video compression technology. Video compression algorithm, MPEG1, MPEG4, such as H.261 and H.264, a lot of the standard used. Improved compression performance. Energy effective motion estimation technique is reduced to the rest of the frame involved in motion compensation.     

快速而有效的块运动估计算法

为了提高基于块匹配的运动估计的速度和精度,提出了一种带中心偏置点检测模式的自适应快速块运动估计算法。该算法根据图像序列的运动向量基于中心偏置分布的特点和相邻块运动向量间的高度相关性,依据块的不同运动内容来确定其搜索起点、搜索范围和搜索策略,从而实现块运动向量的快速而有效地估计。同时,对于大运动块,采用了多侯选者方式,进一步提高了搜索精度。实验结果表明,该算法的搜索速度接近N3SS,N4SS,而搜索精度比它们高,与HSS相似,接近FSBM。     

Dynamic initial search pattern defined on Cartesian product of neighboring motion vectors for fast block-based motion estimation

Block-based motion estimation is widely used in video compression for reducing the temporal data redundancy. However, it is still a main problem to effectively reduce the computational complexity of motion estimation. The median predictor is usually used for initial search center prediction, however it is not always accurate enough, especially for fast motion sequences. In this paper, a novel dynamic initial search pattern algorithm for fast block-based motion estimation is proposed. Based on the observation that the components of the current motion vector are very similar to the corresponding components of its neighboring motion vectors, Cartesian product of neighboring motion vectors is introduced to generate the proposed dynamic initial search pattern (DISP). And then the cross search pattern is employed to search for the best matching block. The number of search points of the proposed DISP is adaptive to the neighboring correlation of the current block. In fact, the proposed DISP can be considered as a generalization of median prediction scheme and it performs better in capturing the best matching block than median prediction. Experiment results show that the proposed DISP method with small cross search pattern can save about 1.71 search points on average compared with adaptive rood pattern search (ARPS) algorithm and can achieve the similar PSNR to full search (FS) algorithm by combining large cross search pattern.     

动态模式的快速运动估计算法

针对H.264视频编码标准中运动估计的高计算复杂度,提出了一种动态模式的快速运动估计算法。该算法通过判断宏块的运动大小及运动方向选择相应的搜索模式;同时对标准中的中值预测进行了改进并提出了一种动态的参考块提前跳过策略。实验结果表明,该算法在保持良好的率失真性能的基础上,减少了运动估计时间,相对于快速全搜索算法FFS以及UMHexagonS算法,该算法分别减少了85.28%和35.29%的运动估计时间。     

一种结合空间预测和CDS的快速块匹配算法

运动估计是根据视频序列中时间上相关的信息估计场景或目标的二维运动向量场的过程. 因为块运动估计的简单性和有效性, 它已经成为目前使用最广泛的运动估计方法. 本文设计了一种结合空间预测和CDS的快速块匹配算法. 若当前块和相邻块的运动相似, 则选择相邻块的运动向量中使当前块的匹配误差最小的一个作为当前块运动向量的预测估计, 再以该预测值为中心, 比较SDSP上搜索点的块匹配误差. 若当前块和相邻块的运动不相关, 则采用CDS算法从原点开始搜索运动向量. 实验结果表明, 本文设计的算法兼顾了搜索速率和精度, 相比N3SS、DS、HEXBS、CDS、CDHS算法, 更好地适用于超分辨率图像复原.     

基于运动矢量空间相关性的H.264分像素运动估计

随着整像素运动估计快速算法的发展,分像素运动估计的计算量在运动估计中所占比重越发明显。为了减少分像素运动估计的计算量,提出了一种利用运动矢量空间相关性来预测整像素运动块,对整像素运动块进行分像素搜索过程跳过的分像素运动估计方法。实验结果表明,该算法与全分像素搜索算法结合使用,在基本保持搜索精度不变的情况下,比单纯的全分像素搜索算法减少60%左右的分像素搜索点。该算法可与其他快速分像素搜索算法结合使用,以获得更好的编码性能。     

Block matching algorithm for motion estimation based on Artificial Bee Colony (ABC)

Block matching (BM) motion estimation plays a very important role in video coding. In a BM approach, image frames in a video sequence are divided into blocks. For each block in the current frame, the best matching block is identified inside a region of the previous frame, aiming to minimize the sum of absolute differences (SAD). Unfortunately, the SAD evaluation is computationally expensive and represents the most consuming operation in the BM process. Therefore, BM motion estimation can be approached as an optimization problem, where the goal is to find the best matching block within a search space. The simplest available BM method is the full search algorithm (FSA) which finds the most accurate motion vector through an exhaustive computation of SAD values for all elements of the search window. Recently, several fast BM algorithms have been proposed to reduce the number of SAD operations by calculating only a fixed subset of search locations at the price of poor accuracy. In this paper, a new algorithm based on Artificial Bee Colony (ABC) optimization is proposed to reduce the number of search locations in the BM process. In our algorithm, the computation of search locations is drastically reduced by considering a fitness calculation strategy which indicates when it is feasible to calculate or only estimate new search locations. Since the proposed algorithm does not consider any fixed search pattern or any other movement assumption as most of other BM approaches do, a high probability for finding the true minimum (accurate motion vector) is expected. Conducted simulations show that the proposed method achieves the best balance over other fast BM algorithms, in terms of both estimation accuracy and computational cost.     

基于线性预测的半像素运动估计

在视频编码系统中,半像素精度的运动估计虽可以明显地改善编码效果,但也因此增加了不少运算量。为了降低运算量和提高半像素运动估计的速度,提出了一种全新的半像素搜索算法(half-pixel motion estimation based on linear prediction,简称BLPHME),其关键思想是通过分析整像素搜索和半像素搜索结果之间的相关性来建立一个线性模型,通过动态调整判决门限,以便预测并跳过那些不能从半像素块匹配搜索中得到好处的块。实验结果表明,该算法不仅可以明显地降低运动估计的运算量,同时还能得到与传统算法非常接近的图像质量和码率。此外,该算法还可以和基于整像素和半像素的快速运动估计算法一起使用,以进一步降低运算量。     

基于时空域相关预测的步长自适应运动估计算法

为了更好地消除视频中空间和时间冗余,快速并有效地获得足够精度的运动矢量,本文提出一种改进的自适应十字搜索算法。本文算法利用时间空间域相关来预测当前块的运动矢量,对于视频的边缘图像采取固定小步长来进行十字搜索,对于图像的非边缘部分则采取由粗到精的方式进行搜索,搜索模板的自适应臂长为预测得到的目标运动矢量的横纵坐标的最大值。通过实验仿真比较传统的自适应十字搜索算法及其他几种经典的运动估计算法,结果表明本文算法增强了搜索预测的准确性,减少了平均每块搜索的次数,提高了搜索速率。     

基于起点预测的不连续十字形快速搜索算法 *

提出了一种基于起点预测的不连续十字形块搜索算法。该算法首先利用图像帧的时间相关性和空间相关性预测出一个点作为不连续十字形搜索模板的初始中心点 ,再根据运动矢量概率分布的中心十字偏置特性,采用不连续十字形搜索模型 ,对运动矢量进行估计 ,得出最佳运动估计结果。在保证图像质量的前提下 ,该搜索算法与完全搜索算法 ( FS)、三步搜索算法 ( TSS)和钻石搜索算法 ( DS)相比 ,搜索速度显著提高。     

一种块匹配的快速运动估计算法

为了减小运动估计算法的计算复杂度及提高视频压缩编码的效率，提出了一种新的快速、有效的块匹配运动估计算法。该算法首先采用多步搜索策略，并利用相邻块的运动矢量来预测当前块的搜索起点，然后用梯度下降的方向来指导搜索方向，以节约计算资源，对于最佳匹配点所在区域，则采用菱形与正方形相结合的模板来进行精细搜索，以提高算法的搜索精度。实验结果证明，该算法在降低计算复杂度的同时，还能有效地保证搜索精度。     

Block-matching algorithm based on an adaptive reduction of the search area for motion estimation

The motion estimation and compensation technique is widely used for video coding applications but the real-time motion estimation is not easy due to its enormous computations. In this paper, a new adaptive reduction of search area for the block-matching algorithm is presented to reduce the computational complexity of the full search block-matching algorithm for low bit-rate video coding. The proposed method exploits the correlation of successive video frames and adjusts the size of search area depending on the displaced block difference and the block classification information in the previous frames of the block. Simulation results show that the proposed algorithm has similar mean square error performance to the full search block-matching algorithm but only requires less a half computational complexity than the full search algorithm.     

一种基于块匹配的鲁棒运动估计算法

详细论述了基于块匹配的鲁棒运动估计算法。跟已有的基于块匹配的运动估计算法比较，首先，我们引入颜色信息来提高运动估计的准确性；其次，在更广泛的意义上运用自适应策略来减少计算量并同时保证算法的鲁棒性；最后，提出的基于预测修正的复合查找方法充分利用了物体运动的全局信息，克服了三步查找算法以及全查找算法的缺点并充分发挥它们二者的优点从而提高查找的效率和匹配精度。实验结果表明基于块匹配的鲁棒运动估计算法具有抗干扰能力强、运动估计准确、计算效率高等优点。     

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。     

An efficient blocking-matching algorithm based on fuzzy reasoning

Due to the temporal and spatial correlation of image sequence, the motion vector of a reference block is highly related to the motion vectors of its adjacent blocks in the same image frame. By using that idea, we propose a novel efficient fuzzy search (EFS) algorithm for block motion estimation. The experimental results show that the EFS performs better than other fast search algorithms, such as TSS, CS, NTSS, FSS, BBGDS, SES, and PSA in terms of picture quality, accuracy, computational complexity, and coding efficiency.     

一种低复杂度的基于进化策略的自适应运动估计方法

为了进一步提高编码质量并能快速编码,提出了一种新的基于进化策略的自适应运动估计算法。鉴于在进化策略中变异操作与正态分布法则对应,是核心算子,为此将进化策略应用于运动估计,提出了一种新的自适应运动估计算法,并第1次将运动方向信息作为变量引入运动估计算法,同时改进了步长自适应控制机制,以便进一步提高算法的收敛速率,同时采用种群规模的自适应控制,降低了算法的复杂度。试验结果表明,该算法的性能与全搜索算法相近,而复杂度略大于三步法。由于其具有低复杂度和进化算法的内在并行性的特点,故该算法适合硬件实现。