一种HEVC帧内快速编码算法

高效视频编码(HEVC)采用编码单元(CU)四叉树的 分割结构,相比H.264/AVC显著地提升了编码效 率,但却使编码复杂度急剧增加。为此,本文提出一种帧内快速编码算法。首先,根据视 频图像纹理复 杂度,提前判断是否进行最大编码单元(LCU)分割。然后,根据空域相邻CU的深度预测当前C U的深度范围, 跳过不必要的计算;最后,根据预测模式被选为最优预测模式的统计特性,去掉可能性小的 帧内预测模式。本文算法在HM14.0的基础上实现。 仿真结果表明,本文算法在全I帧模式下与HM14.0相比,帧内编码时 间平均减少38%,码率(BR)只增加1.41%,峰值信噪比(PSNR)只降低0.29dB,在保证编码性能和视频质量几乎不变的 情况下,本文算法降低了编码的计算复杂度。     

Pure intra mode decision in HEVC using optimized firefly algorithm

High Efficiency Video Coding (HEVC) is the latest encoder that increased the intra modes from 9 to 35 to efficiently handle the contents of the video. The HEVC’s test model (HM) selects the optimal intra mode using the brute force method which increases the complexity of HEVC. This work, firstly, investigates the feasibility of firefly algorithm (FFA) due to its exploration and exploitation characteristics to expedite the intra mode decision in HEVC. Secondly, a novel objective function is formulated for FFA to efficiently compute the brightness for intra modes in FFA. Thirdly, the parameters of FFA are made dynamic to adjust according to the contents of video sequences. Simulation results demonstrate that the nature inspired algorithm, FFA, pays off by saving a minimum of 27% of the total coding time on average and doesn’t sacrifice quality by limiting Bjontegaard delta bit rate (BD-BR) increase to only 0.98% on average.     

Adaptive Scanning for H.264/AVC Intra Coding

In this letter, an adaptive scanning that improves intra coding efficiency in the H.264/AVC standard is proposed. The proposed adaptive scanning utilizes the prediction directions (modes) that include the horizontal and vertical edge information in a block. Depending on the prediction directions, the proposed method uses three scanning methods: zigzag scanning, horizontal scanning, and vertical scanning. In the proposed method, horizontal and vertical scanning are used in vertical and horizontal prediction modes, respectively, and the normal zigzag scanning in the H.264 standard is used in all other intra prediction modes. The proposed method reduces the bit rate by approximately 2.5% compared with H.264/AVC, without the degradation of video quality.     

Low complexity inter coding scheme for Versatile Video Coding (VVC)

The latest coding standard Versatile Video Coding (VVC) developed by the Joint Video Experts Team (JVET) and Video Coding Experts Group (VCEG) was finalized in 2020. By introducing several new coding techniques, VVC improves the compression efficiency by 50% compared with H.265/HEVC. However, the coding complexity increases dramatically, which obstructs it from real-time application. To tackle this issue, a fast inter coding algorithm utilizing coding information is proposed to speed up the coding process. First, by analyzing the coding areas of the neighboring CUs, we predict the coding area of the current CU to terminate unnecessary splitting modes. Then, the temporally optimal coding mode generated during the prediction process is further utilized to shrink the candidate modes to speed up the coding process. Finally, the distribution of neighboring prediction modes are exploited to measure the motion complexity of the current CU, based on which the unnecessary prediction modes can be skipped earlier. Experimental results demonstrate that the proposed method can reduce the coding complexity by 40.08% on average with 0.07 dB BDPSNR decrease and 1.56% BDBR increase, which outperforms the state-of-the-art approach.     

A novel fast intra algorithm for VVC based on histogram of oriented gradient

The latest Versatile Video Coding (VVC) standard incorporates a series of effective and complex new intra coding tools, which obtains superior coding efficiency than the High Efficiency Video Coding (HEVC). However, this makes the intra coding more complicated and time-consuming. A fast algorithm for VVC from two aspects of fast mode decision and fast partition decision is proposed in this paper. For the fast mode decision, the relationship between bins with Histogram of Oriented Gradient (HOG) and intra modes is created for the mode selection, decreasing the planar modes for SATD and RDO. Moreover, we analyze the maximum bins to determine the final modes, and we use the modes of left and upper blocks as a reference for the current CU, which can early terminate RDO. Moreover, a two-step fast partition algorithm is proposed based on HOG for fast partition decision, in which two thresholds are investigated to control the uniformity of textures. The proposed fast algorithm is implemented on the VVC test model, and the experimental results show that it can achieve 69.07% time savings with only 2.96% BDBR increases averagely, which outperforms other relatively existing state-of-the-art methods. Moreover, to convince the universality of our algorithm, we further implement our method in Fraunhofer Versatile Video Encoder (VVenc) and Fraunhofer Versatile Video Decoder (VVdec), which have five settings to control the trade-off between encoding quality and efficiency for intra coding. The fast intra mode decision algorithm and fast partition algorithm decrease the complexity of intra coding for both VTM and VVenc, which shows the efficiency and universality of the proposed fast partition and fast mode decision algorithms.     

A fast algorithm based on gray level co-occurrence matrix and Gabor feature for HEVC screen content coding

To reduce the computational complexity of screen content video coding (SCC), a fast algorithm based on gray level co-occurrence matrix and Gabor feature model for HEVC-SCC, denoted as GGM, is proposed in this paper. By studying the correlation of non-zero number in gray level co-occurrence matrix with different partitioning depth, the coding unit (CU) size of intra coding can be prejudged, which selectively skips the intra prediction process of CU in other depth. With Gabor filter, the edge information reflecting the features of screen content images to the human visual system (HVS) are extracted. According to Gabor feature, CUs are classified into natural content CUs (NCCUs), smooth screen content CUs (SSCUs) and complex screen content CUs (CSCUs), with which, the calculation and judgment of unnecessary intra prediction modes are skipped. Under all-intra (AI) configuration, experimental results show that the proposed algorithm GGM can achieve encoding time saving by 42.13% compared with SCM-8.3, and with only 1.85% bit-rate increasement.     

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。     

Sum-of-gradient based fast intra coding in 3D-HEVC for depth map sequence (SOG-FDIC)

As the latest video coding standard for multi-view plus depth video, 3D-HEVC yields high coding efficiency but at the cost of heavy computational complexity. To reduce the computational complexity, a fast intra coding algorithm based on sum-of-gradient criterion for depth map coding in 3D-HEVC, named SOG-FDIC, is proposed in this paper. Based on the observation that DMM modes and smaller partitioning sizes are rarely used in flat region, sum of gradient is presented to determine whether the current block belongs to the flat region so as to skip unnecessary checking of DMMs and smaller partitioning sizes. Experimental results show that the proposed algorithm can save about 21.8% coding time while keeping almost the same coding efficiency and the reconstructed video quality of depth maps and synthesized views, compared with the original 3D-HEVC. Moreover, it has been verified that the proposed method outperforms the state-of-the-art methods.     

A novel fast intra mode decision for versatile video coding

The latest video coding standard Versatile Video Coding (VVC) obtains superior coding efficiency compared to the High Efficiency Video Coding (HEVC), which is achieved by incorporating more effective and complex new coding tools. In this paper, we propose a novel fast intra mode decision algorithm for VVC, including following two strategies: (1) the correlation between the optimal modes of the adjacent blocks and the modes selected in the rough modes decision (RMD) process is analyzed and applied to reduce the modes in the candidate list; (2) modes in the candidate list are sorted in ascending order according to the modes’ cost calculated in the RMD process. An early termination method is proposed for terminating the optimal prediction mode decision process based on this new order early. These two strategies are incorporated into intra coding to reduce the coding complexity. Since these two strategies do not add any additional computational complexity, the proposed fast algorithm can achieve more complexity reduction. The experimental results show that the complexity reduction of the proposed algorithm is up to 44.74% compared to VVC reference software VTM2.0, and averagely 30.59% encoding time saving with 0.86% BDBR increase.     

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 algorithm based on the sole- and multi-depth texture measurements for HEVC intra coding

In High Efficiency Video Coding (HEVC), intra coding plays an important role, but also involves huge computational complexity due to a flexible coding unit (CU) structure and a large number of prediction modes. This paper presents a fast algorithm based on the sole- and multi-depth texture measurements to reduce the complexity from CU size and prediction mode decisions. For the CU size decision, evaluation results in the CU coding with one and multiple depths are utilized to classify CUs into heterogeneous, homogeneous, depth-prominent and other ones. Fast CU size decisions are made for different kinds of CUs. For the prediction mode decision, the tendencies for different CU sizes are detected based on multiple depths. The number of searching modes is decreased adaptively for the CU size with fewer tendencies. Experimental results show the proposed algorithm by off-line training reduces 53.32% computational complexity, with 1.47% bit-rate increasing.     

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AVS的帧场自适应编码算法研究

介绍了中国音视频编码技术标准AVS中的帧内预测和基于宏块的帧场自适应编码技术.通过分析其中的5种帧内预测模式的空间分布特点,提出了一种新的隔行视频帧内预测模式.实验表明该模式可以在标清、高清隔行视频的帧内预测上获得平均0.24 dB以上的信噪比增益,平均减少3.1%的码流,是一种有效提高编码效率的预测模式.     

3D-HEVC深度图帧内预测快速编码算法

三维高效视频编码在产生了高效的编码效率的同时也是以大量的计算复杂性作为代价的。因此为了降低计算的复杂度,本文提出了一种基于深度学习网络的边缘检测的3D-HEVC深度图帧内预测快速算法。算法中首先使用整体嵌套边缘检测网络对深度图进行边缘检测,而后使用最大类间方差法将得到的概率边缘图进行二值化处理,得到显著性的边缘区域。最后针对处于不同区域的不同尺寸的预测单元,设计了不同的优化方法,通过跳过深度建模模式和其他某些不必要的模式来降低深度图帧内预测的模式选择的复杂度,最终达到减少深度图的编码复杂度的目的。经过实验仿真的验证,本文提出的算法与原始的编码器算法相比,平均总编码时间可减少35%左右,且深度图编码时间平均大约可减少42%,而合成视点的平均比特率仅增加了0.11%。即本文算法在可忽略的质量损失下,达到降低编码时间的目的。     

Fast mode decision algorithm for intra prediction in H.264/AVC with integer transform and adaptive threshold

Compared with other existing video coding standards, H.264/AVC can achieve a significant improvement in compression performances. A robust criterion named the rate distortion optimization (RDO) is employed to select the optimal coding modes and motion vectors for each macroblock (MB), which achieves a high compression ratio while leading to a great increase in the complexity and computational load unfortunately. In this paper, a fast mode decision algorithm for H.264/AVC intra prediction based on integer transform and adaptive threshold is proposed. Before the intra prediction, integer transform operations on the original image are executed to find the directions of local textures. According to this direction, only a small part of the possible intra prediction modes are tested for RDO calculation at the first step. If the minimum mean absolute error (MMAE) of the reconstructed block corresponding to the best mode is smaller than an adaptive threshold which depends on the quantization parameter (QP), the RDO calculation is terminated. Otherwise, more possible modes need to be tested. The adaptive threshold aims to balance the compression performance and the computational load. Simulation results with various video sequences show that the fast mode decision algorithm proposed in this paper can accelerate the encoding speed significantly only with negligible PSNR loss or bit rate increment. This work is supported in part by China National Natural Science Foundation (CNSF) under Project No.60572045, the Ministry of Education of China Ph.D. Program Foundation under Project No.20050698033, and by a Cooperation Project (2005.7– 2007.7) with Microsoft Research Asia.     

基于机器学习的HEVC帧内模式快速决策算法

针对高效视频编码(HEVC)计算复杂度过高的情况, 提出了一种基于机器学习的帧内快速决策算法。根据图像内容的平滑 程度将PU划分成3类,对具有一定平滑度的预测单元(PU)不需要遍历完所有的帧内预测模式 ,从而有效降低算法的计算复杂度。首 先,计算各个PU的左边参考像素方差、上边参考像素方差和总参考像素的方差,以及各个P U采用的最优的帧内预测模式, 这些方差反映了参考像素的平滑程度;然后,利用机器学习软件Weka对得到的数据进行分类 处理,得到分类决策树; 最后,根据决策树来判定各个PU需要测试的帧内模式,再对各个PU 遍历这些帧内模式,确 定最优的模式,减少不必要 预测,从而降低编码复杂度。实验结果表明,本文算法相对于标准的HEVC 15.0编码算法,在高码率的情况下,编码时间平 均节省约16.18%,BD-rate平均升高约0.25%,BD-PSNR平均降低约0.02 dB;在低码率的情况下,编码时 间平均节省约20.75%,BD-rate平均升高 约0.04%,BD-PSNR平均降低约0.00dB。     

结合内容特性与纹理类型的HEVC-SCC帧内预测快速算法

本文提出了一种结合内容特性与纹理类型的HEVC-SCC帧内预测快速算法。利用自然内容和屏幕内容视频DCT变换后系数能量分布不同的特点,结合当前预测单元（Prediction Unit, PU）梯度信息,将编码树单元（Coding Tree Unit, CTU）分成自然内容CTU,简单屏幕内容CTU和复杂屏幕内容CTU。对于自然内容CTU,选择35种传统帧内模式作为候选模式,跳过帧内块复制（Intra Block Copy, IBC）和调色板（Palette mode, PLT）模式;对于简单屏幕内容CTU,选择DC,PLANAR,水平和垂直模式作为候选模式,跳过IBC和PLT模式;对于复杂屏幕内容CTU,选择IBC和PLT模式,跳过其他候选模式。实验结果表明,在全I帧条件下,该算法相较于SCM-8.3可以节省38.55%的编码时间,大幅度降低了编码复杂度的同时只增加了1.82%的码率。      

一种HEVC快速帧内模式判断算法

针对HEVC帧内预测模式判断过程较为复杂的问题,提出了一种快速帧内模式判断算法.通过将35种帧内预测模式进行分级计算,利用其中17种模式即能得出最佳预测模式.实验结果表明,与参考编码算法相比,所提出的帧内模式判断算法可以降低约53％的计算量,且编码压缩率几乎不变.     

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。     

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。