H．264运动估计算法的优化研究

通过对H．264中运动估计的分析,选择合适的快速搜索算法来对H．264算法进行化简,对菱形快速搜索算法、分像素的运动估计算法进行了改进,减少了H．264解码器巨大的计算量。     

基于H.264的内容自适应分数像素运动估计算法

分数像素精确运动估计的改进是整个运动估计模块优化的关键,本文提出了基于H.264的内容自适应分数像素运动估计算法。首先,提出基于平坦区域宏块预测的无效分数像素运动矢量(MV)搜索省略算法(SMBP);然后,改进H.264采用的基于中心的分数像素搜索算法(CBFPS),提出基于预测矢量的增强型菱形模板(EDSP)搜索算法。实验结果表明,内容自适应分数像素运动估计算法比分数像素全搜索算法(FFPS)在峰值信噪比(PSNR)有微小降低(0.095～0.209 dB)的情况下,平均减少了75.6%的分数像素搜索点,整个运动估计模块平均节省了38.5%的计算量。     

H.264中一种新型算法的研究

提出一种快速实现H.264运动估计的算法。该算法在新三步搜索算法的基础上对搜索模板进行了改进,并采用了提前终止搜索策略。实验表明,该算法在保持图象质量和峰值信噪比基本不变的情况下大大减少了搜索点的数目,提高了运动估计的速度。因此,本算法可以有效的提高H.264的编码效率。     

H.264/AVC运动估计算法的硬件结构研究

运动估计是H.264/AVC编码器的重要组成部分,其运算量占据了整个编码器计算时间的60%~90%。对H.264/AVC运动估计的几种快速搜索算法进行分析比较,并在此基础上提出先进的六边形搜索算法。给出运动估计快速搜索算法的一般硬件结构,并在此基础上提出具有流水线并行处理能力的先进六边形搜索算法的硬件结构。实验结果表明：该硬件结构系统工作频率能够达到109.06 MHz,完全能够满足高清视频实时应用的要求。     

基于H.264多参考帧的运动搜索快速算法

提出了一种基于H.264多参考帧的快速整像素运动搜索算法,该算法通过建立多参考帧中的搜索起始点模型和基于多参考帧的六边形搜索,能够有效地降低运动搜索的计算量。实验结果表明,基于多参考帧的快速运动搜索算法在保持有较好编码质量的同时,能够在很大程度上减少H.264多参考帧的运动搜索时间。     

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.     

H．264运动估计算法优化研究

H．264是一种适应于低码率传输的新一代视频压缩标准,但其在获得高性能的同时,也导致了其复杂性很高。运动估计是运算量最大的一部分,对运动估计算法进行优化是提高编码效率的关键。基于此,从运动估计的基本原理入手,对几种典型的快速搜索算法进行了分析比较,在此基础上讨论了H．264标准中运动估计的特点和改进方法,并结合H．264标准的特点和快速搜索原理给出了H．264中运动估计快速算法的优化思路。     

基于分形的深度图序列编码算法

充分利用深度图序列相邻帧间的局部相似性,并结合H.264帧内预测编码算法,提出了一种适用于深度图序列编码的新方法,即深度图序列的I帧编码采用H.264帧内预测结构而P帧编码采用基于分形理论的压缩方法。首先介绍了分形编码的理论基础,然后通过改进非均匀多层次六边形格点整像素运动搜索(UMHexagonS)方法,提出了一种更适用于分形编码的基于运动矢量场的自适应六边形搜索算法,从而形成了基于分形的深度图P帧预测编码结构。实验结果表明:本文提出的编码系统在很大程度上提高了H.264的编码性能,峰值信噪比差值(BDPSNR)平均提高了3.54dB,编码比特率差值(BDBR)平均降低40.98%,同时编码复杂度也大大降低,平均编码时间减少了85.27%。     

基于TMS320DM6437的H.264视频编码器搜索算法的优化及实现

文章以H.264视频压缩编码标准的优化为研究重点,在分析对比以往编码器的优缺点后选择开源的X264编码器作为参考模型,并对其在PC端进行运动估计的快速搜索算法进行优化。最后选取TMS320DM6437的DSP平台作为H.264视频压缩编码器移植平台,最终实现了多平台上的优化与应用。     

H264中的码率控制技术研究及其进展

码率控制是视频编码中的重要技术之一。本文在简要介绍传统的码率控制技术的基础上，着重分析和比较了H.264中的码率控制技术以及近年来提出的多种改进方法，并对H.264的码率控制方法提出了一些改进方向和建议。     

Computationally Optimal Metric-First Code Tree Search Algorithms

Code tree search algorithms find wide applicability in source encoding, channel decoding, pattern recognition, and maximum likelihood sequence estimation. These algorithms search code trees and may be classified as depth-first, breadth-first, and metric-first depending on the search criterion employed. We define here a criterion for metric-first algorithms to be optimal. We show that implementations of metric-first searches proposed heretofore are not optimal, and we propose and analyze two algorithms which are. Experimental data obtained by encoding a voiced speech sound point to superiority of the proposed implementation over earlier versions.     

Rapid code acquisition algorithm employing PN matched filters

The performance of four algorithms using pseudonoise matched filters (PNMFs), for direct-sequence spread-spectrum systems, is analyzed. They are: parallel search with fix dwell detector (PL-FDD), parallel search with sequential detector (PL-SD), parallel-serial search with fix dwell detector (PS-FDD), and parallel-serial search with sequential detector (PS-SD). The operation characteristic for each detector and the mean acquisition time for each algorithm are derived. All the algorithms are studied in conjunction with the noncoherent integration technique, which enables the system to operate in the presence of data modulation. Several previous proposal using PNMF are seen as special cases of the present algorithms     

遗传算法的自适应进化策略及TSP问题的遗传优化

本文研究遗传算法的进化策略，提出了一种在遗传操作层次上将局部搜索方法与基本遗传算法要结合，依据遗传群体的环境参量动态地调整遗传算法的进化策略和控制局部搜索强度的自适应进化策略，并结合货郎担（ＴＳＰ）优化问题介绍其具体实现方法，给出实验结果。     

Performance Analysis of an Expanding-Search Algorithm for Coarse Acquisition of DSSS Signals

For coarse acquisition of Direct Sequence Spread Spectrum (DSSS) signals, a search of the possible code phases is required. In cases such as signal reacquisition, where a priori information is available, the serial search may be abandoned in favor of an expanding search. In this paper, an expanding-search algorithm is presented and compared to the expanding-sweep algorithms which have been treated in the literature. Performance results for the serial-search and the expanding-search algorithms are given. A discussion of the optimality of the serial-search and the expanding-search algorithms is presented. Performance comparisons of the serial search and the expanding search are made for different a priori code phase probability density functions (pdfs) and the results are discussed. A technique for determining when the expanding search is an optimal search algorithm is developed and applied to the performance curves shown previously. The results indicate that the expanding search provides a quantifiable improvement over the serial search when the pdf is somewhat peaked. The results also indicate that in many cases the expanding search may be a more effective search algorithm than the more common expanding sweep.     

3G网中无线接入网的优化设计

为了降低搜索时间，给出了一种新的第三代移动通信网(3G UMTS)中的无线接入模型，并分析了链路费用、简单切换费用和复杂切换费用对总费用的影响。通过仿真，比较了禁忌搜索算法、模拟退火算法和贪婪算法在给出模型下的总费用仿真结果。     

两约束路由问题的近似解法

首先回顾了一些重要的QOS路由算法，然后对关于两约束路由问题(BCP,bi—constraint path problem)的线性搜索算法进行了数学分析，确定了搜索因子的范围和最佳搜索因子的值。基于以上分析，我们给出了BCP和单约束最短路径问题(RSP,restricted shortest path problem)的近似算法，并对算法性能进行了分析；最后，本文研究了采用非线性链路代价函数求解BCP。测试结果表明本文提出的算法是求解BCP和RSP的有效算法。     

Efficient multilevel successive elimination algorithms for block matching motion estimation

The authors present fast algorithms to reduce the computations of block matching algorithms, for motion estimation in video coding. Efficient multilevel successive elimination algorithms are based on the multilevel successive elimination. Efficient multilevel successive elimination algorithms consist of four algorithms. The first algorithm is given by the sum of absolute difference between the sum norms of sub-blocks in a multilevel successive elimination algorithm (MSEA) using the partial distortion elimination technique. By using the first algorithm, computations of MSEA can be reduced further. In the second algorithm, the sum of absolute difference (SAD) is calculated adaptively from large value to small value according to the absolute difference values between pixels of blocks. By using the second algorithm, the partial distortion elimination in the SAD calculation can occur early, therefore the computations of MSEA can be reduced. The second algorithm is useful not only with MSEA, but also with all kinds of block matching algorithms. In the third algorithm, the elimination level of the MSEA can be estimated. Accordingly, the computations of the MSEA related to the level lower than the estimated level can be reduced. The fourth algorithm is, first of all, to search the motion vector over the half sampled search points. At the second search, the authors search the unsampled search points around the tested search points where the motion vector may exist from the first search results. The motion estimation accuracy of the fourth algorithm is nearly 100% and the computations can be greatly reduced.     

基于改进禁止搜索算法的矢量量化码书设计

本文提出了基于改进禁止搜索(TS)算法的矢量量化(VQ)码书设计方法.禁止搜索算法的关键是如何定义一个解以及如何在当前解的基础上生成邻域解.由于码书设计的两个优化准则是最邻近条件和聚类质心条件,本文提出了两种禁止搜索算法的解描述方案,其相应算法分别叫基于码书的禁止搜索(CB-TS)算法和基于聚类划分的禁止搜索(PB-TS)算法.为了提高禁止搜索算法的性能,文中在禁止搜索算法中融入了模拟退火(SA)机制.为了进一步提高码书性能,文中还将码书设计的传统LBG算法融入禁止搜索算法中.结果表明,基于禁止搜索的两种码书设计方案所生成的码书性能都比LBG算法有明显提高.     

Performance analysis of a duplex multicast switch

A multicast switching architecture called a duplex multicast switch is proposed, and several switch control algorithms are developed. A duplex multicast switch, with two point-to-point routing nets, has potential to provide significantly better performance than a simplex multicast switch by reducing the output loadings of routing nets. To fully realize its potential, two call distribution algorithms, cluster distribution and spread distribution, are developed. Cluster distribution is partitioned into partial search cluster distribution and exhaustive search cluster distribution based on search policies, and the performance of the three algorithms is analyzed by the arrival modulation technique. The results show that a spread distribution eliminates most slot contention blocking and achieves near-optimal performance     

An efficient search strategy for block motion estimation usingimage features

Block motion estimation using the exhaustive full search is computationally intensive. Fast search algorithms offered in the past tend to reduce the amount of computation by limiting the number of locations to be searched. Nearly all of these algorithms rely on this assumption: the mean absolute difference (MAD) distortion function increases monotonically as the search location moves away from the global minimum. Essentially, this assumption requires that the MAD error surface be unimodal over the search window. Unfortunately, this is usually not true in real-world video signals. However, we can reasonably assume that it is monotonic in a small neighborhood around the global minimum. Consequently, one simple strategy, but perhaps the most efficient and reliable, is to place the checking point as close as possible to the global minimum. In this paper, some image features are suggested to locate the initial search points. Such a guided scheme is based on the location of certain feature points. After applying a feature detecting process to each frame to extract a set of feature points as matching primitives, we have extensively studied the statistical behavior of these matching primitives, and found that they are highly correlated with the MAD error surface of real-world motion vectors. These correlation characteristics are extremely useful for fast search algorithms. The results are robust and the implementation could be very efficient. A beautiful point of our approach is that the proposed search algorithm can work together with other block motion estimation algorithms. Results of our experiment on applying the present approach to the block-based gradient descent search algorithm (BBGDS), the diamond search algorithm (DS) and our previously proposed edge-oriented block motion estimation show that the proposed search strategy is able to strengthen these searching algorithms. As compared to the conventional approach, the new algorithm, through the extraction of image features, is more robust, produces smaller motion compensation errors, and has a simple computational complexity.