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。     

一种H.264运动估计器的VLSI设计

MPEG4AVC／ITU—T H．264视频编码标准中所采用的多模式运动估计算法与传统的MPEG4、H．263 高级预测模式相比较而言，编码效率和性能都大大提高。但其诸如模式决策等问题却给运动估计器，特别是硬件运动估计器带来非常大的运算复杂度。本文提出一种H．264运动估计器硬件结构，它采用了新的模式决策算法和快速运动估计算法。仿真结果证明，这两种算法不但能使运动估计器降低其硬件实现成本，而且能减少模式决策和运动估计的时间。     

基于H.264的多参考帧快速选择算法

 H.264采用了多参考帧技术,大大提高了预测精度,改善了视频图像质量,然而这种特性同时也带来了很高的计算复杂度.为了降低H.264编码器的计算复杂度,本文提出了一种多参考帧快速选择算法.该算法充分考虑多参考帧中运动矢量的相关性以及中心偏置特性,通过对待选参考帧进行预选择,有效减少了需要进行全搜索的参考帧个数,提高了编码速度.实验结果表明,该算法在保持图像质量和码率变化很小的前提下,运动估计模块编码速度提高了30.91%.     

自适应简单菱形六边形运动估计搜索算法

针对H.264的特点,提出一种快速块匹配搜索算法.该算法充分利用宏块编码模式间的关联特性和运动矢量的统计特征来降低块匹配搜索复杂度。仿真结果表明,该算法在不改变重建图像质量的条件下,大幅度减少了搜索点数,提高了搜索效率,而且避免了DS算法可能陷入局部最佳点的弊端。     

一种基于硬件实现的快速运动估计半像素级搜索算法

研究了在绝对差和准则下的整像素级块匹配和半像素级块匹配的联系，对绝对差和进行了合理的数学曲线拟合，通过数学曲线来预测最小绝对差和所在半像素位置，从而得到半像素级最佳匹配矢量。分析了三种不同的凹函数预测模型，提出了一种适合硬件实现的运动估计快速半像素级搜索算法。该算法直接根据整像素级运动估计的结果来推算半像素级运动估计结果，在很大程度上降低了半像素级运动估计的运算复杂度，从而利用低码率视频编码的实时实现。试验结果表明该算法可获得较好的重建图像质量。该算法利于硬件实现，可以方便地集成到现有的视频编码器中，具有较好的实用价值。     

基于TIDM642的一种H．264插值快速实现方法

H.264视频编码标准正在得到越来越广泛的运用。在H.264中,插值和运动估计的计算复杂度之和大概占到整个视频编码的50%以上。因此,如何降低插值和运动估计的计算复杂度是快速实现H.264的关键所在。针对DM642的硬件架构,尝试了一种新的插值数据结构。经过优化,对于插值过程本身,以及到后来计算运动矢量时的数据缺失引起的CPU数据挂起,都降低到了比较理想的水平。     

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。     

一种基于H.264/AVC的高效块匹配搜索算法

本文针对H.264/AVC的编码特点,提出了一种利用时空域运动相关性的快速块匹配搜索算法.该算法充分利用了视频序列的运动程度与宏块编码模式间的关联特性以及运动矢量的统计特征,明显减少了运动估计的搜索复杂度.实验表明,本文方法的搜索速度分别比FS和DS算法平均提高了77.96%和32.19%;重建图像的PSNR比DS算法平均提高了0.06dB,更接近FS算法的编码质量.     

移动视频终端中H.264快速决策算法的研究及实现

MPEG-4 AVC/ITU-T H.264视频编码标准因其优异的编码效率和性能而被广泛采用,但其模式决策问题导致运动估计器运算复杂度非常大。本文提出一种适合在移动视频终端设备等计算能力有限的应用场合下进行H.264实时编码的快速模式决策算法的实现方法。该方法具有计算复杂度低和逻辑简单的特点。仿真结果证明,本方法在编码质量降低较小的情况下,能够减少80%以上的编码时间。     

基于图像拼接的全帧视频稳定算法

结合改进的比特平面匹配运动估计方法和图像拼接技术得到一种全帧视频稳定算法.基于菱形搜索的灰阶编码比特平面局部求精匹配方法在保证匹配精度的前提下,利用二进制布尔运算和菱形搜索降低了运动估计的计算复杂度,得到近似最优的估计精度.针对静态、平面场景视频序列,算法利用图像拼接技术得到全帧稳定视频.仿真实验验证了算法的有效性.     

基于H.263标准的图象压缩算法的研究

简要介绍了基于H．263标准的运动图象压缩应用和核心算法，对于低带度上的可视电话等应用，为使此算法实时，有效，运动估计，DCT及量化算法是关键，特别是运动估计算法的选择极大影响到计算速度和压缩率。     

一种用于视频分割的快速运动估计方法

本文在考虑视频分割特点的基础上,提出了一种分层块匹配的运动估计方法,这处估计方法具有较快的估计速度和较高的峰值信噪比。用这种方法对一帧图像进行一次运行估计约需0．1秒,可以用于实时的视频分割系统中。实验证明这是一种性能良好的运动估计方法。     

计算能力可伸缩的运动估计率失真优化

不同硬件设备具有不同的计算能力,能否在任意给定计算能力约束下达到最好的编码效率,是当前视频编码研究领域的一个极具挑战性问题.同时,随着分块结构越来越灵活的编码标准不断出现（如：HEVC,H.264等）,运动估计不得不反复地应用在大小不同的各种分块上,导致其对编码总体计算复杂度的影响愈加重要.在此背景下,本文提出了一种针对运动估计的计算能力可伸缩（Complexity scalable）优化算法.我们通过对运动估计过程中预测失真度和计算复杂度的变化规律建模,发现根据各宏块的特性设置不同的预测失真度阈值可以优化地分配计算资源.而该阈值的大小则恰恰是各宏块的最小预测失真度加上一个由复杂度约束统一决定的偏移量.有鉴于此,我们进一步构造了计算能力可伸缩的优化运动估计算法,在不增加额外计算量的前提下,快速地得到各个宏块所对应的优化阈值,并完成运动估计.通过实验分析,该算法不仅具备自动适应不同计算复杂度约束的能力,而且在任意给定的复杂度约束下,都能提供优化的编码性能.     

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.     

Video Block Motion Estimation Based on Gray-Code Kernels

Motion in modern video coders is estimated using a block matching algorithm that calculates the distance and direction of motion on a block-by-block basis. In this paper, a novel fast block-based motion estimation algorithm is proposed. This algorithm uses an efficient projection framework that bounds the distance between a template block and candidate blocks. Fast projection is performed using a family of highly efficient filter kernels-the gray-code kernels-requiring only 2 operations per pixel per kernel. The projection framework is combined with a rejection scheme which allows rapid rejection of candidate blocks that are distant from the template block. The tradeoff between computational complexity and quality of results can be easily controlled in the proposed algorithm; thus, it enables adaptivity to image content to further improve the results. Experiments show that the proposed adaptive algorithm outperforms other popular fast motion estimation algorithms.     

亚象素运动估值快速算法

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。文中提出了一种亚象素精度视频运动估值的快速算法，根据半象素精度运动估值的中间结果，直接推算出更高精度的运动估值。该算法为高精度亚象素运动估值的研究提供了算法保证。     

A multilevel successive elimination algorithm for block matchingmotion estimation

An efficient algorithm is proposed to reduce the computation cost of block matching algorithms for motion estimation in video coding. Based on a new insight in block matching algorithms, we extend the successive elimination algorithm to a multilevel case. By using the sum norms of the blocks and the subblocks, tighter and tighter decision boundaries can be obtained for eliminating the search positions. The efficiency of the proposed algorithm combined with the full search algorithm and several fast search algorithms is verified by simulation results.     

A hierarchical design methodology for full-search block matching motion estimation

Many useful DSP algorithms have high dimensions and complex logic. Consequently, an efficient implementation of these algorithms on parallel processor arrays must involve a structured design methodology. Full-search block-matching motion estimation is one of those algorithms that can be developed using parallel processor arrays. In this paper, we present a hierarchical design methodology for the full-search block matching motion estimation. Our proposed methodology reduces the complexity of the algorithm into simpler steps and then explores the different possible design options at each step. Input data timing restrictions are taken into consideration as well as buffering requirements. A designer is able to modify system performance by selecting some of the algorithm variables for pipelining or broadcasting. Our proposed design strategy also allows the designer to study time and hardware complexities of computations at each level of the hierarchy. The resultant architecture allows easy modifications to the organization of data buffers and processing elements-their number, datapath pipelining, and complexity-to produce a system whose performance matches the video data sample rate requirements.     

小数像素运动估计快速算法

高精度的匹配和补偿可以减少预测误差，提高压缩视频图像的质量。提出了一种小数像素精度视频运动估计的快速算法，根据半像素精度运动估计的中间结果，直接推算出最高精度的运动估计。根据该算法可以快速得到任意小数像素精度的运动估计。     

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.