一种HEVC帧内预测编码CU结构快速选择算法

为了提升高效视频编码(HEVC) 帧内预测编码部分的编码效率,提出了一种HEVC帧内预测编码编码单元(CU)结构快速选择算 法。算法通过 对CTU(coding tree unit)四叉树结构的遍历过程进行优化,设计了两种不同的最优CU结 构快速决策算 法,分别从最大划分深度和最小划分深度开始遍历,并在每一步遍历之前,判断是否提前终 止遍历操作。 同时,在对每个CTU进行求解时,依据其纹理复杂度和当前编码状态,从两种算法中选择出 最优快速决策 算法对其进行求解。在HM 15.0的基础上实现了提出的快速选择算法 。实验结果表明,本文算法能够在 保证编码性能的同时,降低31.14%的编码时间,提高了HEVC的编码效 率。     

Self-learning residual model for fast intra CU size decision in 3D-HEVC

As an extension of the High Efficiency Video Coding (HEVC) standard, 3D-HEVC requires to encode multiple texture views and depth maps, which inherits the same quad-tree coding structure as HEVC. Due to the distinct properties of texture views and depth maps, existing fast intra prediction approaches were presented for the coding of texture views and depth maps, respectively. To further reduce the coding complexity of 3D-HEVC, a self-learning residual model-based fast coding unit (CU) size decision approach is proposed for the intra coding of both texture views and depth maps. Residual signal, which is defined as the difference between the original luminance pixel and the optimal prediction luminance pixel, is firstly extracted from each CU. Since residue signal is strongly correlated with the optimal CU partition, it is used as the feature of each CU. Then, a self-learning residual model is established by intra feature learning, which iteratively learns the features of the previously encoded coding tree unit (CTU) generated by itself. Finally, a binary classifier is developed with the self-learning residual model to early terminate CU size decision of both texture views and depth maps. Experimental results show the proposed fast intra CU size decision approach achieves 33.3% and 49.3% encoding time reduction on average for texture views and depth maps with negligible loss of overall video quality, respectively.     

基于时空相关性的HEVC帧间模式决策快速算法

新一代的高效率视频编码标准HEVC采用编码树单元（CTU）四叉树划分技术和多达10种的帧间预测单元（PU）模式,有效地提高了编码压缩效率,但也极大地增加了编码计算复杂度。为了减少编码单元（CU）的划分次数和候选帧间PU模式个数,提出了一种基于时空相关性的帧间模式决策快速算法。首先,利用当前CTU与参考帧中相同位置CTU、当前帧中相邻CTU的深度信息时空相关性,有效预测当前CTU的深度范围。然后,通过分析当前CU与其父CU之间的最佳PU模式空间相关性,以及利用当前CU已估计PU模式的率失真代价,跳过当前CU的冗余帧间PU模式。实验结果表明,提出的算法与HEVC测试模型（HM）相比,在不同编码配置下降低了52%左右的编码时间,同时保持了良好的编码率失真性能;与打开快速算法选项的HM相比,所提算法进一步降低了30%左右的编码时间。     

A Fast Intra‐Prediction Method in HEVC Using Rate‐Distortion Estimation Based on Hadamard Transform

A fast intra‐prediction method is proposed for High Efficiency Video Coding (HEVC) using a fast intra‐mode decision and fast coding unit (CU) size decision. HEVC supports very sophisticated intra modes and a recursive quadtree‐based CU structure. To provide a high coding efficiency, the mode and CU size are selected in a rate‐distortion optimized manner. This causes a high computational complexity in the encoder, and, for practical applications, the complexity should be significantly reduced. In this paper, among the many predefined modes, the intra‐prediction mode is chosen without rate‐distortion optimization processes, instead using the difference between the minimum and second minimum of the rate‐distortion cost estimation based on the Hadamard transform. The experiment results show that the proposed method achieves a 49.04% reduction in the intra‐prediction time and a 32.74% reduction in the total encoding time with a nearly similar coding performance to that of HEVC test model 2.1.     

基于决策树的HEVC SCC帧内编码快速算法

为减少HEVC屏幕内容编码的编码时间,提高编码 效率,本文提出了一种基于决策树的HEVC屏幕内容帧内编码快速 CU划分和简单PU模式选择的算法。对视频序列特性分析,提取有效的特征值,生成决策树模 型。使用方差、梯度信息熵和 像素种类数用于生成CU划分决策树,使用平均非零梯度、像素信息熵等用于生成PU模式分类 决策树。在一定深度的决策 树模型中,通过对相应深度的CU的特征值的计算快速决策当前CU的划分与PU模式的类型。这 种利用决策树做判决的算法 通过减少CU深度和PU的模式遍历而降低编码复杂度,达到快速帧内编码的效果。实验结果表 明,与HEVC屏幕内容的标 准算法相比,该算法在峰值信噪比(PSNR)平均下降0. 05 dB和码率 平均增加1.15%的情况下,能平均减少30.81% 的编码时间。     

一种基于时空相关性的编码单元深度快速分级判决算法

新一代视频编码标准HEVC采用编码树单元(CTU) 结构进行编码,通过遍历比较所有不同深度编码 单元(CU)的率失真代价值得到最佳编码单元,在显著提升编码效率的同时,计算复杂度增 加数倍。为此,本文提出了一种基于时空相关的编码单元深度快速分级判决算法,通过量化 分析时 空相邻CTU/CU之间相关性权重,利用已编码时空相邻CTU/CU的最佳深度预测当前CTU/CU可能 的深度范围(DR)和深度值, 跳过和提前终止不必要的深度计算。仿真结果表明,在不同的编码配置条件下,本文算法在 保证编码性能的同时,平均可节省40%以上的编码时间 ,极大地降低了计算复杂度。     

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.     

Rough mode cost–based fast intra coding for high-efficiency video coding

The quadtree-based coding unit (CU) and transform unit (TU) structure, as well as various prediction units (PUs) of HEVC, considerably increase encoding complexity in intra coding and inter coding. This paper proposes a rough mode cost (RMC)-based algorithm for accelerating CU/TU depth decisions and PU mode decisions in HEVC intra coding. For CU depth decisions, RMC values are used for the fast determination of CU partition. In the case of PU mode decisions, modes with higher RMCs are removed from the candidate list to reduce the number of test modes. For TU depth decisions, the TU partition of the mode with the least RMC is used to determine the TU partitions of remaining modes. The proposed TU partitioning method demonstrates superior performance to the default method in reference software. The proposed algorithm can reduce encoding time by approximately 51% on average, with a 0.69% increase in the Bjøntegaard-Delta (BD) rate.     

Efficient prediction of CU depth and PU mode for fast HEVC encoding using statistical analysis

High Efficiency Video Coding (HEVC) adopts complex quadtree-structured CU (coding unit) and PU (prediction unit) modes. Thus, the search process for optimal modes causes high computational complexity in HEVC. To solve this problem, a fast coding algorithm is proposed. Thirteen neighboring CTUs (Coding Tree Unit) are divided into three classes with the k-means method, and are selectively used as the reference CTUs to calculate the predicted CU depth levels for the current CTU. Additionally, for every CU depth, we skip some rarely used PU modes to reduce the complexity of the PU selection algorithm. Experimental results show that compared with the HEVC reference software, our algorithm can achieve 56.71% time saving with Low Delay Configuration profile and 59.76% with Random Access Configuration profile, whereas values of BDBR (Bjontegaard Delta Bit Rate) are only 1.0517% and 0.9918%, respectively. Compared with five state-of-the-art algorithms, the proposed algorithm has significant encoding time reduction with good bitrate performances.     

面向VVC帧内编码的快速CU划分和角度模式决策

多功能视频编码(versatile video coding,VVC)是 最新的视频编码标准,与高效视频编 码(high efficiency video coding,HEVC)相比进一步提高了压缩效率,但由于引入了包括 二 叉树和三叉树在内的多类树结构,同时帧内角度模式从35种增加到67种,导致编码复杂度剧 增。为了降低计算复杂度,本文提出了一种基于快速编码单元(coding unit,CU)划分和角度 模式决策的VVC帧内编码算法。首先根据自适应标准差阈值对CU纹理复杂度进行分类,初 步缩减划分模式列表;然后采用Sobel梯度算子确定纹理方向,跳过非最优划分模式;最后 根据统计结果筛选淘汰掉概率小于2%的 角度模式。实验结果表明,与VTM-2.1相比,该算 法能节省51.05%的编码时间,BDBR (Bjontegarrd delta bit rate)仅上升1.98 %。     

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 %).     

x265的低复杂度帧内编码快速算法

为了降低x265的帧内编码复杂度,减少编码所需时间,本文针对新一 代高效视频编码标准(HEVC)帧内编码单元(CU)划分以 及预测单元(PU)模式选择的快速算法进行研究。采用经典的差分矩阵计算纹理复杂度,提出 了一种根据当前编码单元子块的纹理复杂 相似度与其编码所需要的总比特数以及量化参数之间的关系作为提前终止CU划分的判决 条件,通过增加SATD的计算进一 步减少PU模式选择的RDO候选列表的个数从而减少率失真代价计算的快速算法。实验结果 表明,与x265的标准算法相比, 该算法在平均峰值信噪比(PSNR)仅减少0.028dB和码率平均增加1.27%的情况下,能够平均减少32.34%的帧内编 码时间。     

一种低复杂度的HEVC帧内快速编码算法

为了降低高效视频编码(HEVC)帧内编码复杂度,提出一种HEVC帧内快速编码算法。根据视频图像的纹理复杂性,提前跳过或者中止部分尺寸的编码单元(CU)的划分,减少CU深度遍历区间;同时,根据粗选过程后预测模式和代价值的统计特性采用阈值法或者梯度模式直方图法进一步筛选掉粗选后可能性较小的预测模式,从而减少最后进行率失真(RD)代价计算的帧内预测模式数量,进一步降低编码复杂度。实验结果表明,本文算法与HEVC原始平台相比,在全I帧编码模式下编码时间平均减少42.20%,码率(BR)上升约1.75%,峰值信噪比(PSNR)降低了0.108dB,有利于实时应用。     

Low complexity encoder optimization for HEVC

High Efficiency Video Coding (HEVC) improved the coding efficiency significantly. Compared to its predecessor H.264/AVC, it can provide equivalent subjective quality with more than 57% bit rate reduction. However, the improvement on coding efficiency is obtained at the expense of much more intensive computation complexity. In this paper, based on an overall analysis of computation complexity at the HEVC encoder, a low complexity encoder optimization scheme is proposed by reducing the number of available candidates for evaluation in terms of the intra prediction mode decision, early termination of coding unit (CU) splitting and adaptive reference frame selection. With the proposed scheme, the rate distortion optimization (RDO) technique of HEVC can be implemented in a low-complexity way for complexity-constrained encoders. Experimental results demonstrate that, compared with the original HEVC reference encoder implementation, the proposed optimization scheme can achieve more than 40% complexity reduction on average with coding performance degradation as only 0.43% which can be ignorable.     

高效率视频编码帧内预测编码单元划分快速算法

高效率视频编码(HEVC)采用基于编码单元(CU)的四叉树块分区结构,能灵活地适应各种图像的纹理特征,显著提高编码效率,但编码复杂度大大增加,该文提出一种缩小深度范围且提前终止CU划分的快速CU划分算法。首先,在学习帧中,基于Sobel边缘检测算子计算一帧中各深度边缘点阈值,缩小后面若干帧中CU遍历的深度范围;同时,统计该帧中各CU划分为各深度的率失真(RD)代价,计算各深度的RD代价阈值。然后,在后续视频帧中,利用RD代价阈值在缩小的深度范围内提前终止CU划分。为了符合视频内容的变化特性,统计参数是周期性更新的。经测试,在平均比特率增加仅1.2%时,算法时间平均减少约59%,有效提高了编码效率。     

Accelerating QTMT-based CU partition and intra mode decision for versatile video coding

The H.266/VVC achieves about 50% bitrate saving compared to its predecessor H.265/HEVC at the expense of exponentially increased computational complexity. The most efficient but complex technique for H.266/VVC intra frame coding is the QuadTree with a nested Multi-type Tree encoding structure (QTMT), which usually requires traversing the Rate-Distortion (R-D) cost of each partition and each mode for the best option. To alleviate such computational burden while preserving the coding efficiency as much as possible, this paper develops a multi-feature guided Fast CU Partition (FCP) and Laplacian guided Fast Mode Selection (FMS) to accelerate the intra QTMT decision together. For FCP, we regard the CU partition as a classification problem and adopt the Support Vector Machine (SVM) for its low-complexity implementation; after evaluating the contribution of a set of features, three representative features of video textures are selected and used to train the SVM model. Additionally, an advanced technique is applied by adopting a soft decision in SVM for a more flexible trade-off between the complexity and R-D performance. For FMS, we utilize the Laplace operator to determine the most probable directions of the current CU and skip half of the candidate modes for runtime saving. Experimental results demonstrate that the proposed FCP reduces the encoding time of H.266/VVC by 51.03% with 1.65% Bjøntegaard Delta Bit-Rate (BDBR) increase; the proposed FMS reduces the encoding time by 12.68% with 0.09% BDBR loss. Their direct combination and advanced combination finally lead to 54.84% encoding time reduction with 1.74% BDBR increase and 40.39% encoding time reduction with 1.33% BDBR increase, respectively, outperforming state-of-the-art approaches significantly.     

Multi-class support vector machine-based fast algorithm for 3D-HEVC depth video intra coding

The recursive splitting process of largest coding unit (LCU) and the mode search process of coding unit imposed enormous computational complexity on encoder. A multi-class support vector machine-based (MSVM) fast coding unit (CU) size decision algorithm for 3D-HEVC depth video intra-coding was proposed. The algorithm included two steps: off-line training and fast CU size and mode decision. In the process of off-line training, a MSVM model was constructed, where the texture complexity of current LCU, the optimal partition depth of its spatial neighboring LCU and co-located LCU in texture video were treated as feature vectors, and the optimal partition depth of LCU was utilized as corresponding class label. In the process of fast CU size and mode decision, features of LCU were extracted before cod-ing a LCU, then, a MSVM model was used to predict the class label. Finally, the class label that represents the largest parti-tion depth of the current LCU was employed to terminate the CU recursive splitting process and CU mode search process. Experimental results show that the proposed algorithm saves the encoding time of 3D-HEVC by 35.91% on average, and the encoding time of depth video by 40.04% on average, with negligible rendered virtual view image degradation.     

Fast intra-encoding algorithm for High Efficiency Video Coding

The emerging High Efficiency Video Coding (HEVC) standard provides equivalent subjective quality with about 50% bit rate reduction compared to the H.264/AVC High profile. However, the improvement of coding efficiency is obtained at the expense of increased computational complexity. This paper presents a fast intra-encoding algorithm for HEVC, which is composed of the following four techniques. Firstly, an early termination technique for coding unit (CU) depth decision is proposed based on the depth of neighboring CUs and the comparison results of rate distortion (RD) costs between the parent CU and part of its child CUs. Secondly, the correlation of intra-prediction modes between neighboring PUs is exploited to accelerate the intra-prediction mode decision for HEVC intra-coding and the impact of the number of mode candidates after the rough mode decision (RMD) process in HM is studied in our work. Thirdly, the TU depth range is restricted based on the probability of each TU depth and one redundant process is removed in the TU depth selection process based on the analysis of the HEVC reference software. Finally, the probability of each case for the intra-transform skip mode is studied to accelerate the intra-transform skip mode decision. Experimental results show that the proposed algorithm can provide about 50% time savings with only 0.5% BD-rate loss on average when compared to HM 11.0 for the Main profile all-intra-configuration. Parts of these techniques have been adopted into the HEVC reference software.     

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%。      

Fast encoder decision for texture coding in 3D-HEVC

As a 3D extension of the High Efficiency Video Coding (HEVC) standard, 3D-HEVC is developed to improve the coding efficiency of multi-view video. However, the improvement of the coding efficiency is obtained at the expense of a computational complexity increase. How to relieve the computational burden of the encoder is becoming a critical problem in applications. In this paper, a fast encoder decision algorithm to encode the dependent texture views is proposed, where two strategies to accelerate encoder decision by exploiting inter-view correlations are utilized. The first one is an early merge mode decision algorithm, and the second one is an early CU splitting termination algorithm. Experimental results show that the proposed algorithm can achieve 47.1% encoding time saving with overall 0.1% BD-rate reduction compared to HTM (3D-HEVC test model) version 7 under the common test condition (CTC). Both of the two strategies have been adopted into the 3D-HEVC reference software and enabled as a default encoding process under CTC.