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.     

一种新的H.264多参考帧快速搜索算法

H.264/AVC是目前最新的视频编码国际标准.在H.264/AVC中,由于采用了多参考帧,运动估计部分的复杂度大大增加了.虽然JVT采用的快速运动估计(FME)提案能极大地提高搜索速度,但只是加快了一帧的搜索速度.本文在FME基础上提出了一种新的多参考帧快速搜索算法(FMRSA),它利用当前块周围的块信息来预测将要搜索的参考帧的范围,并在具体搜索过程中运用提前中断的方法加快整个搜索过程.实验证明本算法比标准快速搜索法搜索5个参考帧能在PSNR降低不超过0.05dB、码率增加不超过2.32%的情况下节省至少56.5%的时间.     

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.     

Successive elimination algorithm for motion estimation

The correspondence presents a fast exhaustive search algorithm for motion estimation. The basic idea is to obtain the best estimate of the motion vectors by successively eliminating the search positions in the search window and thus decreasing the number of matching evaluations that require very intensive computations. Simulation results demonstrate that although the performance of the proposed algorithm is the same as that using the exhaustive search, the computation time has been reduced significantly     

Pel-recursive motion estimation algorithm

A new pel-recursive motion estimation algorithm for video coding applications is presented. The derivation of the algorithm is based on recursive least-squares estimation that minimises the mean-square prediction error. A comparison with the modified steepest-descent gradient estimation technique algorithm shows significant improvement in terms of mean-square prediction error performance     

基于运动矢量场的双迭代全局运动估计方法

提出了一种基于运动矢量场的双迭代全局运动估计方法，该方法用两个最小二乘迭代过程来去除局部运动区域对全局运动估计的干扰。第一个迭代使用一个递减的百分比阈值来排除局部运动区域；第二个迭代过程使用一个固定的绝对阈值来检测完整的伞局运动区域并估计运动模型参数。实验结果表明双迭代法进行伞局运动估计的结果更加准确和稳定。     

Efficient motion estimation algorithm for bidirectional predictionscheme

A novel block matching algorithm based on successive refinement using motion correlation is presented, which estimates more accurate forward and backward motion vectors for interpolative prediction as well as forward and backward predictions in bidirectionally predictive-coded pictures. Experimental results show that this algorithm achieves good performance in PSNR and subjective quality with low computational complexity     

AVS的自适应提前终止运动估计算*

非对称十字形多层次六边形格点搜索(UMHexagonS)是AVS视频编码中优秀的搜索算法,但仍然存在计算量大的缺点,为了提高编码速度,提出了基于自适应阈值的提前终止算法。首先,自适应的选择SAD阈值,然后引入搜索和SAD计算的提前终止判断;其次,在模式选择中引入了代价值提前比较,该方法对运动缓慢的序列改善较明显。实验表明,在帧间预测不采用帧内预测模式的情况下,优化后的算法在保证视频质量的基本不变的前提下,编码速度平均提高为原来的2倍多。     

Content-adaptive motion estimation algorithm for coarse-grain SVC

A joint model of scalable video coding (SVC) uses exhaustive mode and motion searches to select the best prediction mode and motion vector for each macroblock (MB) with high coding efficiency at the cost of computational complexity. If major characteristics of a coding MB such as the complexity of the prediction mode and the motion property can be identified and used in adjusting motion estimation (ME), one can design an algorithm that can adapt coding parameters to the video content. This way, unnecessary mode and motion searches can be avoided. In this paper, we propose a content-adaptive ME for SVC, including analyses of mode complexity and motion property to assist mode and motion searches. An experimental analysis is performed to study interlayer and spatial correlations in the coding information. Based on the correlations, the motion and mode characteristics of the current MB are identified and utilized to adjust each step of ME at the enhancement layer including mode decision, search-range selection, and prediction direction selection. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of SVC while maintaining nearly the same rate distortion performance as the original encoder.     

A complexity-bounded motion estimation algorithm

The full search motion estimation algorithm for video coding is a procedure of high computational cost. For this reason, in real-time low-power applications, low-cost motion estimation algorithms are viable solutions. A novel reduced complexity motion estimation algorithm is presented. It conjugates the reduction of computational load with good encoding efficiency. It exploits the past history of the motion field to predict the current motion field. A successive refinement phase gives the final motion field. This approach leads to a sensible reduction in the number of motion vector that have to be tested. The complexity is lower than any other algorithm algorithms known to the authors, in the literature, it is constant as there is no recursivity in the algorithm and independent of any search window area size. Experimental evaluations have shown the robustness of the algorithm when applied on a wide set of video sequences-a good performance compared to other reduced complexity algorithms and negligible loss of efficiency versus the full search algorithm.     

Improved motion estimation time using a combination of dynamic reference frame selection and residue-based mode decision

Motion estimation using multiple reference frames is widely used as the basis for recent video coding standards (eg. H.264/AVC) to achieve increased coding efficiency. However, this increases the complexity of the encoding process. In this paper, a new technique for efficient motion estimation is proposed. A combination of multiple reference frame selection and image residue-based mode selection is used to improve motion estimation time. By dynamic selection of an initial reference frame in advance, the number of reference frames to be considered is reduced. In addition, from examination of the residue between the current block and reconstructed blocks in preceding frames, variable block size mode decisions are made. Modified initial motion vector estimation and early stop condition detection are also adopted to speed up the motion estimation procedure. Experimental results compare the performance of the proposed algorithm with a state of the art motion estimation algorithm and demonstrate significantly reduced motion estimation time while maintaining PSNR performance.     

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.     

Sorting-based partial distortion search algorithm for motion estimation

A fast motion-estimation algorithm based on partial block distortion for sorted significant pixels is proposed. The proposed algorithm can obtain very accurate motion vectors with a reduced computational load. Experimental results show that the proposed scheme gives the same performance as the full search, while it is about 6-10 times faster than the full search.     

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.     

A new block-based motion estimation algorithm

The conventional motion estimation algorithms used in digital television coding can roughly be classified into two categories, namely the block-matching method and the recursive method. Each of them has its own strong points. In this paper, a new type of block-based motion estimation algorithm is presented, which is based on the block-recursive (gradient) method and makes use of some of the merits of the block-matching method. For a moderate translational motion, motion estimation with a subpel precision can conveniently be obtained with only a couple of recursive searches, and for a violent or complicated motion which cannot be estimated by any block-based algorithm, the local minimum of prediction errors can always be found. Our experiments show that the proposed algorithm is efficient and reliable, and obviously superior to the conventional block-recursive algorithms and the fast block-matching algorithms. The performance of the proposed algorithm tends almost to the optimum of the full search algorithm with the same estimation precision, but the computational effort is much less than that of the full search algorithm.     

一种改进的解隔行运动估计算法

简要介绍了基于目标的运动估计算法，它用于隔行扫描到逐行扫描的转换以及帧率的变换。在此算法的基础上提出了一种简化其运动模型分配的方法，从而减少了一定的计算量，并对视觉效果几乎没有影响。     

Evolutionary strategy search algorithm for fast block motion estimation

The evolutionary strategy search (ESS) algorithm is a novel method for implementing fast block motion estimation (ME) using evolutionary strategy (ES). ESS uses a combination of ideas based on existing search strategies and employs a novel (1+/spl sigma//spl lambda/) ES implementation. It is essentially a succession of random searches, but by controlling the placement and distribution of these searches in a simple way, it proves possible to achieve comparable motion vector accuracy to the more established ME strategies, but with enhanced convergence speed.     

Enhanced partial distortion search algorithm for block motion estimation

A block matching algorithm for fast motion estimation based on partial block distortion is presented, which can reduce the computational complexity and provide accurate motion vectors. Simulation results show that the proposed algorithm offers a performance very close to that of the full search scheme and is about 18 to 22 times faster.     

Early termination algorithm for 2BT block motion estimation

A simple algorithm to reduce the computational complexity of two bit transform (2BT) block motion estimation is presented. The difference between pixel intensity and the mean value is added and compared to a certain threshold value. The proposed algorithm is much faster than the conventional 2BT algorithm, while maintaining visual quality.