H.264宏块模式的一种快速判决方案

H.264采用了可变块运动估计和率失真优化模式判决,极大地增加了编码器的复杂度.本文利用H.264参考软件对时间/空间相邻宏块模式之间的相关性进行了分析,相应地提出了一种快速算法以降低模式判决的运算复杂度.利用已编码相邻宏块的运动信息和模式类型比率信息预测当前宏块的候选模式类型,然后采用部分率失真优化决定当前宏块的编码模式.如果某些模式不在候选模式之列,就不再对其做运动估计.如果相邻宏块的平均失真超过了预定阈值,当前宏块就采用常规的率失真优化模式判决.实验结果表明,对于A、B类测试图像序列,采用本文方案可以明显降低编码复杂度,而编码质量只有轻微的下降.     

基于局部残差复杂度的快速帧间模式选择

针对H.264传统帧间模式选择算法的高复杂度,提出了一种适合各种视频分辨率格式的快速帧间模式选择算法。该算法基于局部残差复杂度(local residual complexity,LRC),通过给局部残差复杂度设定阈值来决定宏块的活跃度,再根据宏块的活跃度选出候选的帧间模式,由此进行率失真优化(Rate-distortion Optimization,RDO)计算,从而减少了不必要帧间模式的RDO计算,取得了较高的编码效率。实验结果表明,与JM18.4默认的帧间模式选择算法相比,该算法在峰值信噪比和码率基本不变的前提下,可以平均减少大约60%的运动估计时间。     

基于H.264待编码宏块纹理特性的快速搜索算法

为减小H.264帧间预测运动估计算法复杂度,提出了一种基于待编码宏块纹理特性以排除部分搜索位置的方法.该方法可以大大减少待搜索位置的数目,缩短帧间预测时间.同时给出了一种基于宏块纹理的自适应快速搜索算法.实验表明,新算法在重建图像质量没有明显下降的前提下,编码速度有所提高.     

H.264的帧间宏块模式选择算法

H.264中定义了7种不同大小的帧间宏块模式,为了提高编码效率,编码时对每一种宏块模式都进行运动搜索,并利用率失真优化(RDO)分别计算编码代价,选择编码代价最小的模式作为帧间编码模式,但是计算量非常大,导致运动估计速度缓慢,很难实现实时编码。本文提出一种选择宏块模式的快速算法,通过宏块模式编码代价的比较,提前确定宏块模式,从而逐步减少不必要的宏块搜索和RDO计算。实验结果表明,此方法与全宏块模式搜索相比较,图像质量和码流只有少量变化,而编码速度有显著提高。     

基于DCT域的任意分辨率视频可伸缩编码

空间分辨率可伸缩编码能够满足网络视频对不同码率的要求以及不同用户显示终端的需求,成为近几年研究热点.由此提出一种基于DCT域准卷积的任意分辨率下采样方法,该方法通过分析子块与宏块DCT系数之间的关系,实现了由子块DCT系数预测宏块DCT系数,通过低通滤波器截取预测的宏块低频DCT系数,实现任意分辨率下采样.实验证明:该方法适合诸如H.264、AVS等基于DCT变换的视频编码标准,且提供灵活的空间可伸缩能力.     

基于感知的多视点视频编码宏块模式选择快速算法

多视点视频编码(MVC)采取可变块模式选择技术和 多参考帧技术显著提高了编码的压缩效率,但同时带来了巨大的 编码计算复杂度。为了降低MVC的计算复杂度,提出基于感知的快速MVC宏块模式选择 算法。基于人眼视觉感知的特点,利用视觉恰可察觉失真(JND)的概念建立MVC宏块的最优模 式和JND的联系,并利用该联系确定早期结束最优宏块模式选择过程的阈值,根据当前编码 宏块的JND与阈值的 关系自适应地减少每个编码宏块的模式搜索次数,进而减少MVC的方向搜索和参考帧搜索的 次数,以降 低编码的复杂度,提高MVC速度。实验结果显示,对于不同运动特性、内容、纹理信息、相 机间距和图像 尺寸的测试序列,提出的快速算法在率失真性能几乎不变的情况下平均节约76.00% 编码时间。     

多搜索中心的运动估计快速算法

块大小可变的运动估计方法能提高视频编码性能,但也增加了计算时间.为了加快运动估计计算,本文提出了一种基于多搜索中心预测和搜索范围动态调整的快速算法.多搜索中心预测方法对当前宏块时间和空间上相邻块的运动向量进行分析,得出多个预测向量作为运动估计的搜索中心.相比传统预测方法,多搜索中心预测最高可提高约14.6%的预测精度....     

H.264的帧间宏块模式选择算法

H.264中定义了7种不同大小的帧间宏块模式，为了提高编码效率，编码时对每一种宏块模式都进行运动搜索，并利用率失真优化（RDO）分别计算编码代价，选择编码代价最小的模式作为帧间编码模式，但是计算量非常大，导致运动估计速度缓慢，很难实现实时编码。本文提出一种选择宏块模式的快速算法，通过宏块模式编码代价的比较，提前确定宏块模式，从而逐步减少不必要的宏块搜索和RDO计算。实验结果表明，此方法与全宏块模式搜索相比较，图像质量和码流只有少量变化，而编码速度显著提高。     

一种用于块运动估计的匹配准则函数块特征匹配函数

本文提出了一种新的块运动估计匹配准则函数块特征匹配(BFM)函数,可以用于视频压缩的一些国际标准,如H.261,H.263,MPEG1,MPEG2,HDTV的编解码器中。在这些视频压缩国际标准中视频系统编码器的复杂性最主要取决于运动估计算法。实时的块匹配运动估计的VLSI实现需要考虑以下几个方面:在给定搜索域内运动搜索的复杂度;每次块匹配运算的匹配计算复杂度;每次块匹配运算需要从帧存读取到运动估计处理器的数据量大小;实时硬件实现的适用性.仿真表明BFM算法非常简单有效,可以大大降低相应的块匹配计算复杂度、匹配运算时数据传输时间.BFM函数便于并行实现,从而可以有效地缩短视频编码器的编码时间。本文还详细地给出了BFM函数与其它常用匹配准则函数的比较结果.     

适宜于质量可伸缩帧间编码的快速算法

根据质量可伸缩编码的特征,提出一种适合于中粒度质量可伸缩视频编码增强层的帧间快速编码算法。首先根据基本层宏块的模式和率失真值预测当前宏块编码模式采用的顺序;然后根据编码结构提出Direct编码方式判断,根据层间相关性提出了层间方式判断,利用空间相关性提出了相邻方式判断,最后根据已预测的模式顺序编码当前宏块,并利用这3种判断提前终止以提高编码速度。实验结果证明,与标准算法相比,所提算法的计算复杂度平均降低了68%,同时对编码质量和比特率几乎没有影响。     

Computation-aware fast motion estimation for H.264/AVC using image indexing

The key to designing a real-time video coding system is efficient motion estimation, which reduces temporal redundancies. The motion estimation of the H.264/AVC coding standard can use multiple references and multiple block sizes to improve rate-distortion performance. The computational complexity of H.264 is linearly dependent on the number of allowed reference frames and block sizes using a full exhaustive search. Many fast block-matching algorithms reduce the computational complexity of motion estimation by carefully designing search patterns with different shapes or sizes, which have a significant impact on the search speed and distortion performance. However, the search speed and the distortion performance often conflict with each other in these methods, and their high computational complexity incurs a large amount of memory access. This paper presents a novel block-matching scheme with image indexing, which sets a proper priority list of search points, to encode a H.264 video sequence. This study also proposes a computation-aware motion estimation method for the H.264/AVC. Experimental results show that the proposed method achieves good performance and offers a new way to design a cost-effective real-time video coding system.     

Fast multiresolution motion estimation algorithms for wavelet-based scalable video coding

Motion estimation and compensation in wavelet domain have received much attention recently. To overcome the inefficiency of motion estimation in critically sampled wavelet domain, the low-band-shift (LBS) method and the complete-to-overcomplete discrete wavelet transform (CODWT) method are proposed for motion estimation in shift-invariant wavelet domain. However, a major disadvantage of these methods is the computational complexity. Although the CODWT method has reduced the computational complexity by skipping the inverse wavelet transform and making the direct link between the critically sampled subbands and the shift-invariant subbands, the full search algorithm (FSA) increases it. In this paper, we proposed two fast multiresolution motion estimation algorithms in shift-invariant wavelet domain: one is the wavelet matching error characteristic based partial distortion search (WMEC-PDS) algorithm, which improves computational efficiency of conventional partial distortion search algorithms while keeping the same estimate accuracy as the FSA; another is the anisotropic double cross search (ADCS) algorithm using multiresolution-spatio-temporal context, which provides a significantly computational load reduction while only introducing negligible distortion compared with the FSA. Due to the multiresolution nature, both the proposed approaches can be applied to wavelet-based scalable video coding. Experimental results show the superiority of the proposed fast motion estimation algorithms against other fast algorithms in terms of speed-up and quality.     

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.     

Efficient Mode Decision Algorithm Based on Spatial,Temporal, and Inter‐layer Rate‐Distortion Correlation Coefficients for Scalable Video Coding

The layered coding structure of scalable video coding (SVC) with adaptive inter‐layer prediction causes noticeable computational complexity increments when compared to existing video coding standards. To lighten the computational complexity of SVC, we present a fast algorithm to speed up the inter‐mode decision process. The proposed algorithm terminates inter‐mode decision early in the enhancement layers by estimating the rate‐distortion (RD) cost from the macroblocks of the base layer and the enhancement layer in temporal, spatial, and inter‐layer directions. Moreover, a search range decision algorithm is also proposed in this paper to further increase the motion estimation speed by using the motion vector information from temporal, spatial, or inter‐layer domains. Simulation results show that the proposed algorithm can determine the best mode and provide more efficient total coding time saving with very slight RD performance degradation for spatial and quality scalabilities.     

Effective computation-aware algorithm by inter-layer motion analysis for scalable video coding

Scalable video coding incorporated with computation-aware ability achieves quality as well as being computation scalable. This paper presents a computation-aware algorithm for scalable video coding with spatial/quality scalability aiming for the best trade-off between rate distortion performance and computational consumption. We first observe and analyze and then establish a model for the motion vector difference relationship between the scalable base and enhancement layers. By using the modeling results, a linear algorithm for computation distribution is thus proposed to allocate the computation for each macroblock in the enhancement layer. In addition, the rate distortion costs of the base layer are also taken into account for the computation allocation process in order to further improve the coding performance. The simulation results demonstrate that our proposed computation-aware algorithm not only accomplishes better rate distortion performance than other works under the same computational constraints, but also achieves less computation necessities.     

Fuzzy quantization based bit transform for low bit-resolution motion estimation

This study proposes a novel fuzzy quantization based bit transform for low bit-resolution motion estimation. We formalize the procedure of bit resolution reduction by two successive steps, namely interval partitioning and interval mapping. The former is a many-to-one mapping which determines motion estimation performance, while the latter is a one-to-one mapping. To gain a reasonable interval partitioning, we propose a non-uniform quantization method to compute coarse thresholds. They are then refined by using a membership function to solve the mismatch of pixel values near threshold caused by camera noise, coding distortion, etc. Afterwards, we discuss that the sum of absolute difference (SAD) is one of the fast matching metrics suitable for low bit-resolution motion estimation in the sense of mean squared errors. A fuzzy quantization based low bit-resolution motion estimation algorithm is consequently proposed. Our algorithm not only can be directly employed in video codecs, but also be applied to other fast or complexity scalable motion estimation algorithms. Extensive experimental results show that the proposed algorithm can always achieve good motion estimation performances for video sequences with various characteristics. Compared with one-bit transform, multi-thresholding two-bit transform, and adaptive quantization based two-bit transform, our bit transform separately gains 0.98 dB, 0.42 dB, and 0.24 dB improvement in terms of average peak signal-to-noise ratio, with less computational cost as well.     

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．     

Coding statistics based fast mode decision for multi-view video coding

Reduction of high computational complexity of multi-view video coding (MVC) is necessary for realization in consumer electronics. Since mode decision is one of the key computational bottlenecks of multi-view video encoders, this paper proposes a coding statistics based fast mode decision algorithm. First of all, a rate–distortion cost based fast DIRECT mode decision algorithm early terminates the mode decision process if possible. Next, the candidates for Inter modes are reduced by taking the advantage of the correlation between an optimal mode and motion cost. The proper thresholds to reduce the candidates for the above two fast algorithms can be easily derived from exponential functions at run time. Finally, motion vector difference based motion characteristics is referred to further speed up the mode decision process of Inter modes. The experimental results show that the proposed scheme reduces up to 70.82% of encoding time with negligible degradation of RD performance.     

Flexible distribution of complexity by hybrid predictive-distributed video coding

There is currently limited flexibility for distributing complexity in a video coding system. While rate-distortion-complexity (RDC) optimization techniques have been proposed for conventional predictive video coding with encoder-side motion estimation, they fail to offer true flexible distribution of complexity between encoder and decoder since the encoder is assumed to have always more computational resources available than the decoder. On the other hand, distributed video coding solutions with decoder-side motion estimation have been proposed, but hardly any RDC optimized systems have been developed.To offer more flexibility for video applications involving multi-tasking or battery-constrained devices, in this paper, we propose a codec combining predictive video coding concepts and techniques from distributed video coding and show the flexibility of this method in distributing complexity. We propose several modes to code frames, and provide complexity analysis illustrating encoder and decoder computational complexity for each mode. Rate distortion results for each mode indicate that the coding efficiency is similar. We describe a method to choose which mode to use for coding each inter frame, taking into account encoder and decoder complexity constraints, and illustrate how complexity is distributed more flexibly.     

一种基于子搜索格雷码核的快速视频块运动估计算法

快速视频块运动估计是视频编码中的一个重要问题。在格雷码核( GCK)算法的基础上,提出一种改进的子搜索格雷码核( Sub-GCK)算法。理论上的计算复杂度分析表明：提出的子搜索格雷码核算法的运算量大约为原始格雷码核算法的22.1%。实验比较了子搜索格雷码核算法、原始格雷码核算法和其他几种常见的运动估计算法的编码性能,结果显示：新算法在保证编码质量的前提下,有效降低了运动估计时间,时间约为原始格雷码核算法的41.9%。