低复杂度的多视点视频编码宏块模式决策算法

为了降低多视点视频编码(MVC)的计算复杂度,提出了一种基于全局-局部率失真代价的低复杂度宏块模式决策算法。首先根据宏块候选模式的块尺寸和率失真代价特点,将所有候选模式分为大尺寸模式(Skip/Direct、Inter16×16和Intra16×16)和小尺寸模式(Inter16×8、Inter8×16、Inter8×8、Intra8×8和Intra4×4);接着统计已编码帧中这两类宏块模式的平均率失真代价,并利用这些平均率失真代价计算当前帧宏块模式决策的全局率失真代价;最后利用得到的全局率失真代价,并结合当前宏块已估计模式的局部率失真代价和空间邻近宏块的模式信息提前终止模式决策,具体包括对大尺寸宏块模式进行提前判定以及对小尺寸候选模式进行逐级选择。实验结果表明:与MVC参考代码中的全搜索模式决策算法相比,本文算法在时域预测视点和视点域预测视点上分别节省了74%和82%的平均编码时间,同时保持了良好的编码率失真性能;与现有模式决策快速算法相比,本文算法降低了更多的编码时间,并具有更好的编码率失真性能。     

基于相邻宏块率失真代价的JMVC快速算法

为了降低JMVC(Joint Multiview Video Coding联合多视点视频编码)编码复杂度,提出一种根据前一编码宏块参考方向和率失真代价,提前终止JMVC模式选择的算法。该算法首先获取前一宏块的率失真代价和参考方向,随后根据前一宏块参考方向为当前宏块的搜索设定一个率失真代价门限,最后利用此门限实现提前终止。实验结果显示,相比于JMVC原始算法,本文算法的编码质量没有下降,而编码时间节省了34.86%~54.23%。算法可以在保证编码质量的前提下,有效地较低编码复杂度。     

3D-HEVC合并模式快速判决方法研究

基于高效视频编码的3D视频编码（3D-HEVC）是目前正在研究的新一代3D视频编码标准。为降低3D-HEVC中模式选择的计算复杂度,根据非独立视点纹理图中合并模式采用率高的特点,该文提出了一种3D-HEVC合并模式快速判决方法。在B帧中,分析了当前编码单元（CU）与视点方向参考帧中参考块间编码模式的相关性;在P帧中,分析了位于相邻划分深度的CU间编码模式的相关性。根据分析的视点间和划分深度间的相关性设计快速判决条件,预判采用合并/合并-跳过模式编码的CU,判别出的CU在模式选择过程中只检查相关的候选预测模式,从而降低计算复杂度。实验结果表明,与3D-HEVC原始算法相比,该文算法能够在率失真性能损失很小的前提下,平均节省11.2%的总编码时间和25.4%的非独立视点纹理图的编码时间。      

应用于多视点视频压缩的多参考B帧快速编码算法

基于H.264平台就多视点视频压缩中多参考帧技术存在计算复杂度高的现状,根据多视点视频序列特性,提出了一种针对多参考B帧的快速多视点视频编码压缩算法。新算法改进了多参考帧列表策略,并结合多视点视频序列的时空域相关性特性,提出了适用于多视点视频编码的参考帧列表调整策略。此外,还针对多种块模式编码引入了块模式预判策略。新算法在保证率失真性能的基础上,有效地降低了计算复杂度,提高了多视点视频编码速度。虽然本文是基于M-Picture编码结构实现了新算法,但它同样适用于其它应用多参考B帧预测技术的多视点视频编码结构中。     

H.264/AVC帧内预测模式的快速选择算法

H.264/AVC帧内预测技术采用率失真优化策略进行最优化编码模式选择,提高了I帧的编码效率,但同时也提高了计算复杂度。提出了一种帧内预测模式的快速选择算法,基于亮度块的方向特性,通过一些复杂度不大的计算,选择少数几个可能性较大的预测模式进行率失真代价计算,得到最佳亮度预测模式,并以SATD计算代替率失真代价计算选择最佳色度预测模式,降低了计算复杂度,提高了编码速度。实验结果表明,提出的算法在保证图像质量的同时,编码时间平均降低了48%,而码率增加很小。     

一种H.264/AVC帧内预测模式的快速选择算法

H.264/AVC帧内预测技术采用率失真优化策略进行最优化编码模式选择,提高了I帧的编码效率,但同时也提高了计算复杂度。本文提出了一种帧内预测模式的快速选择算法,基于亮度块的方向特性,通过一些复杂度不大的计算,选择少数几个可能性较大的预测模式进行率失真代价计算,得到最佳亮度预测模式,并以 计算代替率失真代价计算选择最佳色度预测模式,降低了计算复杂度,提高了编码速度。实验结果表明,本文提出的算法在保证图像质量的同时,编码时间平均降低了48%,而码率增加很小。     

结合深度信息的多视点视频编码快速模式选择算法

多视点视频加深度(MVD,multi-view video plus depth)的编码格式包含多个纹理视频序列及其对应的深度图,深度图与对应的纹理视频具有相似的边缘信息。传统的编码模式不考虑两者的联系,单独编码导致复杂度高、编码时间过长。因此,合理利用深度图与纹理图的相似性进行编码,可以有效降低编码复杂度,同时应该确保编码质量不受影响。本文利用深度图的这一特点辅助纹理视频的编码,提出一种帧间快速模式选择算法,充分利用深度图与纹理图之间的相似性,建立一种联合复杂度模型,根据模型得到每个宏块的复杂度。对于复杂度低的宏块,在计算率失真代价之前跳过编码中一些不必要的模式,从而降低编码复杂度。实验表明,本文提出的快速模式选择算法,在保证率失真性能基本不变的情况下,能减少60.57%的编码复杂度,并最高能减少80.64%的编码时间。     

基于模式分组的帧内预测模式快速选择算法

针对高效率视频编码(HEVC)帧内预测中增加的预测模式引起的的粗选择模式(RMD)与率失真优化(RDO)算法计算复杂度高的问题。本文充分利用候选模式集中排列第一的预测模式与最优预测模式之间的强相关性,提出了一种基于模式分组的帧内预测模式快速选择算法,有效的降低了HEVC帧内预测算法的计算复杂度。实验表明本文所提出的算法与HEVC的测试模型HM10.0相比,在保证视频质量和码率基本不变的前提下(码率仅增加了0.78%,Y-PSNR只降低了0.12dB),减少了41.8％的编码时间,提高了编码效率。     

多视点编码中一种快速的模式选择方法

在多视点视频编码中,多尺寸的运动估计和视点估计被用来选择宏块的最优编码模式。这些技术大大提高了编码效率,但是却带来了庞大的计算复杂度,从而影响了多视点视频编码的广泛应用。提出了一种新的模式选择的快速算法,利用了相邻视点的模式相关性来减少执行不需要的模式。实验表明,所提出的快速模式选择算法在不降低编码效率的同时可以显著降低计算复杂度。     

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。     

利用纹理结构的HEVC快速帧内模式选择算法

高性能视频编码（HEVC）是刚确立的最新一代的视频编码标准。对于帧内编码,HEVC最大的特点是采用了从64×64至8×8的编码单元划分和35种帧内预测模式,HEVC通过遍历所有的分块和帧内预测模式,选取最优的预测方式,这种帧内预测方式在提高预测精度的同时也大大增加了编码的计算复杂度。为了降低帧内预测的计算复杂度,HM2.0版以上的HEVC测试软件采用一种基于两步预测的快速帧内模式选择算法。在此基础上本文首先提出了一种基于纹理方向的快速粗选方案,减少参与计算的粗选模式数,进而提出基于结构相关的决策方法,利用同质图像区域的纹理相似性,减少参与率失真代价函数计算的候选模式数量,进一步降低了帧内预测计算复杂度。实验结果表明,本文所提出的快速算法,在保持编码质量基本不变的条件下,可以使基于两步预测的快速帧内模式选择时间缩短25%。      

Efficient early direct mode decision for multi-view video coding

Multi-view video coding (MVC) uses various prediction modes and exhaustive mode decision to achieve high coding efficiency. However, the introduced heavy computational complexity becomes the bottleneck of the practical application of MVC. For this, an efficient early Direct mode decision for MVC is proposed in this paper. Based on the observation that the Direct mode is highly possible to be the optimal mode, the proposed method first computes the rate distortion (RD) cost of the Direct mode and compares this RD cost value with an adaptive threshold for providing an early termination chance as follows. If this RD cost value is smaller than the adaptive threshold, the Direct mode will be selected as the optimal mode and the checking process of the remaining modes will be skipped; otherwise, all the modes will be checked to select the one with the minimum RD cost as the optimal mode. Note that the above-mentioned adaptive threshold is determined as the median prediction value of a set of thresholds, which are derived by using the spatial, temporal and inter-view correlations between the current macroblock (MB) and its neighboring MBs, respectively. Experimental results have demonstrated that the proposed method is able to significantly reduce the computational complexity of MVC with negligible loss of coding efficiency, compared with the exhaustive mode decision in MVC.     

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.     

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.     

Low-Complexity Intra-Coding Scheme for HEVC

Compared with H.264/AVC, the latest video standard High Efficiency Video Coding (HEVC) known as H.265 improves the coding efficiency by adopting the quadtree splitting structure which is flexible in representing various textural and structural information in images. However, the computational complexity is dramatically increased, especially in the intra-mode decision process owing to supporting more partitions and modes. In this paper, we propose a low-complexity algorithm for HEVC intra-coding, which consists of a fast coding unit (CU) size decision (FCUSD) method and a fast prediction unit (PU) mode decision (FPUMD) method. In FCUSD, unnecessary CU sizes are skipped early according to the depth level of neighboring CUs and the rate distortion (RD) cost threshold derived from the former coded frame. In FPUMD, the PU mode and RD cost correlations between different depth levels are utilized to terminate unnecessary candidate modes. Experimental results demonstrate that the proposed algorithm can achieve about 50.99 % computational complexity reduction on average with 1.18 % BD-rate increase and 0.08 dB BD-psnr loss.     

基于结构张量的H.266帧内预测快速算法

新一代视频编码标准H.266将帧内预测模式从35种扩展到67种,提高预测准确率的同时大大增加了编码的计算复杂度。本文根据视频内容纹理方向和帧内预测模式选择相关性强的特点提出了一种基于结构张量的H.266帧内预测模式快速选择算法,以编码单元CU为单位,计算其结构张量矩阵,再依据结构张量奇异值分解后得到的特征向量来确定当前CU的纹理方向,缩小候选模式的选择范围,减少进行代价计算的模式数量。实验结果表明,在全I帧条件下,该算法相较于H.266 VTM-7.3标准平台在节省17.28%编码时间的同时只增加1.12%的码率,有效地降低了编码复杂度。      

Fast CU size and prediction mode decision method for HEVC encoder based on spatial features

In the high-efficiency video coding (HEVC) standard, intra prediction has higher computational complexity compared with H.264/AVC (advanced video coding) because of increasing the number of intra prediction modes and also higher number of coding unit (CU) sizes. The HEVC encoder evaluates 35 prediction modes on five possible prediction unit (PU) sizes to find the one with the minimum rate–distortion cost. Although this approach improves coding efficiency, it is very time-consuming. In this paper, we propose a fast intra prediction method to reduce the complexity of I-frame coding. The proposed method consists of three stages which is based on smoothness spatial feature. In the first stage, a measure is introduced to estimate CU smoothness by using sum of absolute differences (SAD) among CU pixels in four directions. By considering that a smooth region can be predicted with larger CUs, when the measured smoothness parameter is lower than a predefined threshold, only the prediction modes in the current CU are evaluated. In the second stage, the number of intra prediction modes is reduced based on the calculated SADs in the previous stage. In the last stage, if the first three candidate modes resulted from rough mode decision stage in the previous PU and the current PU are similar, then the best mode prediction of the previous PU is selected as the best candidate mode. Experimental results indicate that the proposed method can reduce the coding time on average to 43 % and maintain coding video quality, whereas bitrate increases negligibly (0.5 %).     

Fast depth map mode decision based on depth–texture correlation and edge classification for 3D-HEVC

The 3D extension of High Efficiency Video Coding (3D-HEVC) has been adopted as the emerging 3D video coding standard to support the multi-view video plus depth map (MVD) compression. In the joint model of 3D-HEVC design, the exhaustive mode decision is required to be checked all the possible prediction modes and coding levels to find the one with least rate distortion cost in depth map coding. Furthermore, new coding tools (such as depth-modeling mode (DMM) and segment-wise depth coding (SDC)) are exploited for the characteristics of depth map to improve the coding efficiency. These achieve the highest possible coding efficiency to code depth map, but also bring a significant computational complexity which limits 3D-HEVC from real-time applications. In this paper, we propose a fast depth map mode decision algorithm for 3D-HEVC by jointly using the correlation of depth map-texture video and the edge information of depth map. Since the depth map and texture video represent the same scene at the same time instant (they have the same motion characteristics), it is not efficient to use all the prediction modes and coding levels in depth map coding. Therefore, we can skip some specific prediction modes and depth coding levels rarely used in corresponding texture video. Meanwhile, the depth map is mainly characterized by sharp object edges and large areas of nearly constant regions. By fully exploiting these characteristics, we can skip some prediction modes which are rarely used in homogeneity regions based on the edge classification. Experimental results show that the proposed algorithm achieves considerable encoding time saving while maintaining almost the same rate-distortion (RD) performance as the original 3D-HEVC encoder.     

采用联合特征的H.266/VVC屏幕内容快速模式选择算法

新一代视频编码标准H.266/VCC针对屏幕内容编码引入帧内块复制、调色板等预测模式,在提高编码效率的同时也带来了巨大的计算复杂度。本文采用角点、水平/垂直活动度和平均颜色亮度差联合特征对屏幕内容视频帧和当前编码单元（Coding Unit, CU）进行分类,将视频帧分为低对比度屏幕视频帧和高对比度屏幕视频帧,将CU细分为自然内容背景CU、屏幕内容背景CU和屏幕内容前景CU,进而对CU模式进行选择性跳过,减少模式选择代价。实验结果显示,在全帧内的条件下,该算法与开启IBC和PLT的H.266/VVC VTM-7.3标准相比,在码率仅增加1.21%的情况下节省了26.41%的编码时间,降低了编码复杂度。