考虑视频内容的H.265/HEVC帧层码率分配算法

为了保证一定视频质量下编码器输出的码率符合给定的目标码率,提出一种考虑视频内容特性的H.265/HEVC帧层码率分配算法。首先从率失真理论分析的角度推导出影响输出码率的主要因素,然后根据视频编码原理,预测出帧内容复杂度参数,从而建立一种更有效的帧层码率分配算法。实验结果表明,所提算法可以使帧层目标码率与编码码率保持更好的一致性,且重构视频质量平均提高了0.103 dB。     

Rate control for hierarchical B-frames in H.264/AVC

Hierarchical B-frames can bring high coding performance when introduced into H.264/AVC.However,the traditional rate control schemes can not work efficiently in such new coding framework.This article presents a rate control algorithm for hierarchical B-frames in H.264/AVC.Taking the feature of the dyadic hierarchical coding structure into consideration,the proposed algorithm includes group of pictures(GOP)layer,temporal layer and frame layer bits allocation.After frame layer bits allocation is complete,frame layer quantization parameters(QP)determination strategy is responsible for calculating the final QP.Experimental results show that compared with other rate control algorithms,the proposed one can improve the coding performance and reduce the mismatch of target bit rate and real bit rate.     

一种基于立体视觉显著性的多视点视频比特分配方法

针对多视点立体视频压缩编码,提出了一种基于立 体视觉显著性的比 特分配方法。研究综合利用多视点立体视频数据中场景的运动、深度以及深度边缘信息提取 人眼感兴趣区 域(ROI)的方法;然后根据ROI的划分结果优化区域比特分配。实验结果表 明,本文提出的算法能有效提 高ROI区域的编码性能,同时整体视频的率失真性能有一定程度的提高。     

Floop: An efficient video coding flow for unmanned aerial vehicles

Under limited transmission conditions, many factors affect the efficiency of video transmission. During the flight of an unmanned aerial vehicle (UAV), frequent network switching often occurs, and the channel transmission condition changes rapidly, resulting in low-video transmission efficiency. This paper presents an efficient video coding flow for UAVs working in the 5G nonstandalone network and proposes two bit controllers, including time and spatial bit controllers, in the flow. When the environment fluctuates significantly, the time bit controller adjusts the depth of the recursive codec to reduce the error propagation caused by excessive network inference. The spatial bit controller combines the spatial bit mask with the channel quality multiplier to adjust the bit allocation in space to allocate resources better and improve the efficiency of information carrying. In the spatial bit controller, a flexible mini graph is proposed to compute the channel quality multiplier. In this study, two bit controllers with end-to-end codec were combined, thereby constructing an efficient video coding flow. Many experiments have been performed in various environments. Concerning the multi-scale structural similarity index and peak signal-to-noise ratio, the performance of the coding flow is close to that of H.265 in the low bits per pixel area. With an increase in bits per pixel, the saturation bottleneck of the coding flow is at the same level as that of H.264.     

一种基于预测模式差值的HEVC信息隐藏算法

针对当前HEVC视频信息隐藏算法对视频码率和质 量影响较大等问题,结合HEVC编码标准中 帧内预测模式的特点,提出一种基于帧内预测模式差值的HEVC视频信息隐藏算法。对于连续 两个帧内4×4亮度块预测编码过程中具有方向性的33种预测模式,建立隐秘信息与 预测模式差值的映射关系,根据拉格 朗日率失真模型调制预测模式完成隐秘信息的嵌入。为了保证隐秘信息的嵌入容量,对于连 续两个无方向 性的planar模式或DC模式,根据隐秘信息修改其值实现隐秘信息的嵌入。信息的提取过程, 只需对码流中 的预测模式解码即可。实验结果表明,隐秘信息的嵌入对视频序列的影响较小,亮度分量的 峰值信噪比 (PSNR)值平均下降约0.05dB,对码率 影响仅在1.1%以下,隐秘信息嵌入前后的结构相似度(SSIM)值均 在0.94以上。因此,本文算法能很好保证视频的主客观质量。     

Perceptually-lossless image coding based on foveated-JND and H.265/HEVC

Removing perceptual redundancy plays an important role in image compression. In this paper we develop a foveated just-noticeable-difference (FJND) model to quantify the perceptual redundancy in the image and integrate it in the H.265/HEVC intra encoding framework to provide a perceptually lossless image coding solution. Different to the conventional JND models, our proposed FJND model considers the relationship between contrast masking effect and the foveation properties of HVS. Furthermore, to achieving the perceptually lossless coding, the FJND model is integrated in the H.265/HEVC framework by determining the quantization parameter to ensure that the resulting distortion is no larger than the FJND threshold. The experiments demonstrate that the proposed method effectively improves the compression performance.     

AVS2视频编码标准技术特色及应用

围绕视频编码核心技术,简单介绍AVS视频编码标准发展历程,详细介绍了最新一代AVS视频编码标准——AVS2(GB/T 33475.2-2016)的核心创新技术,主要包括:灵活的预测划分方式、多假设帧间预测、优化的层次变换设计和自适应环路滤波处理技术以及面向场景视频应用AVS2提出的基于场景建模的高效预测编码技术.和第一代AVS视频编码标准相比,AVS2编码效率提升一倍以上;和同期HEVC/H.265国际标准相比,AVS2在场景视频编码方面有显著优势.另外简单介绍了AVS标准在数字电视广播等行业中的应用情况.     

Adaptive lossless coding scheme of lattice vector quantisation

In the process of quantisation, a lattice vector quantiser (LVQ) generates radius and index sequences. In lossless coding, the radius sequence is run-length coded and then Huffman or arithmetic coded, and the index sequence is represented by fixed binary bits. The author has improved the LVQ lossless coding by removing the redundant information between radius sequence and index sequence. An algorithm is developed that redistributes radius and index sequences. The algorithm adaptively shifts down large indices to smaller values and reduces the index bits. Hence, the proposed LVQ lossless coding method reduces the gap between actual coding bit rates and the optimal bit rate boundary. For a Laplacian source the proposed lossless coding scheme achieves more than 10% of bit reduction at bit rates higher than 0.7 bits/sample over the traditional lossless coding method     

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.     

Novel Rate Control Scheme for Low Delay Video Coding of HEVC

In this paper, a novel rate control scheme for low delay video coding of High Efficiency Video Coding (HEVC) is proposed. The proposed scheme is developed by considering a new temporal prediction structure of HEVC. In the proposed scheme, the relationship between bit rate and quantization step is exploited firstly to formulate an accurate quadratic rate‐quantization (R‐Q) model. Secondly, a method of determining the quantization parameters (QPs) for the first frames within a group of pictures is proposed. Thirdly, an accurate frame‐level bit allocation method is proposed for HEVC. Finally, based on the proposed R‐Q model and the target bit allocated for the frame, the QPs are predicted for coding tree units by using rate‐distortion (R‐D) optimization. We compare our scheme against that of three other state‐of‐the‐art rate control schemes. Experimental results show that the proposed rate control scheme can increase the Bjøntegaard delta peak signal‐to‐noise ratio by 0.65 dB and 0.09 dB on average compared with the JCTVC‐I0094 and JCTVC‐M0036 schemes, respectively, both of which have been implemented in an HEVC test model encoder; furthermore, the proposed scheme achieves a similar R‐D performance to Wang's scheme, as well as obtaining the smallest bit rate mismatch error of all the schemes.     

Adaptive bit allocation scheme for rate control in high efficiency video coding with initial quantization parameter determination

One of the challenges in rate control (RC) lies in how to efficiently determine a target bit rate that will be used for the quantization parameter (Q_p) calculation process during video coding. In this paper, we investigate the issues over the existing bit allocation algorithms for the RC process in High Efficiency Video Coding (HEVC) and propose an complexity-based bit allocation scheme to improve the encoding performance. First, we model the relationship between encoding bit rate and texture complexity by a linear rate function. Second, compared with traditional complexity estimation methods, a more accurate model is proposed to measure the texture complexity considering the spatial–temporal correlations. Third, based on the proposed rate function and texture complexity measurement model, we develop an adaptive bit allocation scheme for RC in HEVC. At the same time, depending on the encoder buffer status, an adaptive Q_p clip range determination algorithm is also developed to achieve the encoding quality smoothness while keeping the bit rate fluctuation at an acceptable level. Then, we exploit to determine the initial Q_p efficiently and adaptively according to video contents. Experimental results demonstrate that the proposed RC algorithm can achieve better rate-distortion (R–D) and rate-control performance than that of the state-of-the-art RC scheme implemented in the HEVC reference software HM11.0.     

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.     

Region-of-interest based rate control for UAV video coding

To meet the requirement of high-quality transmission of videos captured by unmanned aerial vehicles (UAV) with low bandwidth, a novel rate control (RC) scheme based on region-of-interest (ROI) is proposed. First, the ROI information is sent to the encoder with the latest high efficient video coding (HEVC) standard to generate an ROI map. Then, by using the ROI map, bit allocation methods are developed at frame level and large coding unit (LCU) level, to avoid inaccurate bit allocation produced by camera movement. At last, by using a better robustness R-λ model, the quantization parameter (QP) for each LCU is calculated. The experimental results show that the proposed RC method can get a lower bitrate error and a higher quality for reconstructed video by choosing appropriate pixel weight on the HEVC platform.     

一种低复杂度的HEVC码率控制算法

针对HEVC视频编码中帧层比特分配和率失真模型参数自适应更新,提出了一种改进的码率控制算法.该算法引入牛顿法来自适应更新率失真模型的参数;同时提出一种帧层复杂度度量方法,利用图像自身的内容特性来调整帧层比特分配;最后在编码过程中选择合适的量化参数.实验结果表明:与参考算法比较,该算法能大大降低计算复杂度,同时保持良好的码率控制性能,对含有场景突变的视频改进效果尤为明显.     

基于线性模型的分级B帧比特分配改进算法

针对分级B帧编码结构,提出了一种基于比特分配线性模型的码率控制算法.通过实验发现不同时间级B帧平均比特数与P帧比特数呈良好的线性关系,利用此线性关系对B帧进行比特分配可以充分利用不同时间级B帧的特性,提高分级B帧结构码率控制的性能.实验结果表明,该算法与JVT-W042相比,对于大部分内容特性序列,平均△SNR提高0.15 dB以上.     

Dynamic computational complexity and bit allocation for optimizing H.264/AVC video compression

In this work, we present a novel approach for optimizing H.264/AVC video compression by dynamically allocating computational complexity (such as a number of CPU clocks) and bits for encoding each coding element (basic unit) within a video sequence, according to its predicted MAD (mean absolute difference). Our approach is based on a computational complexity–rate–distortion (C–R–D) analysis, which adds a complexity dimension to the conventional rate–distortion (R–D) analysis. Both theoretically and experimentally, we prove that by implementing the proposed approach for the dynamic allocation better results are achieved. We also prove that the optimal computational complexity allocation along with optimal bit allocation is better than the constant computational complexity allocation along with optimal bit allocation. In addition, we present a method and system for implementing the proposed approach, and for controlling computational complexity and bit allocation in real-time and off-line video coding. We divide each frame into one or more basic units, wherein each basic unit consists of at least one macroblock (MB), whose contents are related to a number of coding modes. We determine how much computational complexity and bits should be allocated for encoding each basic unit, and then allocate a corresponding group of coding modes and a quantization step-size, according to the estimated distortion (calculated by a linear regression model) of each basic unit and according to the remaining computational complexity and bits for encoding remaining basic units. For allocating the corresponding group of coding modes and the quantization step-size, we develop computational complexity–complexity step–rate (C–I–R) and rate–quantization step-size–computational complexity (R–Q–C) models.     

An efficient motion vector coding scheme based on minimum bitrateprediction

Motion vector coding efficiency is becoming an important issue in low bitrate video coding because of its increasing relative bit portion. This work presents a new motion vector coding technique based on minimum bitrate prediction. In the proposed scheme, a predicted motion vector is chosen from the three causal neighboring motion vectors so that it can produce a minimum bitrate in motion vector difference coding. Then the prediction error, or motion vector difference (MVD), and the mode information (MODE) for determining the predicted motion vector at a decoder are coded and transmitted in order. Sending bits for the MVD ahead of bits for the MODE, the scheme can minimize the bit amount for the MODE by taking advantage of the fact that the minimum bitrate predictor is used for motion vector prediction. Adaptively combining this minimum bitrate prediction scheme with the conventional model-based prediction scheme, more efficient motion vector coding can be achieved. The proposed scheme improves the coding efficiency noticeably for various video sequences.     

Fast sample adaptive offset algorithm for 360-degree video coding

360-degree video is becoming popular with the development of the virtual reality(VR) technology in recent years. For this kind of video, pictures are projected to a two-dimensional plane. Standard video encoders are used for compression. Due to the projection mapping of the spherical video to the two-dimensional plane video, many conventional coding tools can be adjusted properly for better performance. As the 360-degree videos are high resolution videos, usually 8K resolution videos, the high complexity for encoding 360-degree videos is a problem to be solved urgently, especially for the latest video standard H.265/HEVC. Sample adaptive offset (SAO) is a new tool adopted in H.265/HEVC. It can reduce ringing artifacts and achieve higher coding efficiency. But it also introduces high computational complexity, especially on high resolution videos. In this paper, a fuzzy control based fast SAO method is proposed to reduce the high computational complexity in SAO encoding process according to the characteristics of the ERP format video. Compared with the original algorithm in the reference software HM 16.14, experimental results show that the proposed method can reduce about 73% SAO encoding time on average under the common test conditions with negligible loss.     

面向HEVC的Golomb-Rice编码参数自适应策略

为了进一步降低高性能视频编码(HEVC)的输出码率,针对基于上下文的自适应算术编码(CABAC),提出了一种改进算法.利用大尺寸变换单元(TU)和变换跳过模式系数块大值系数较多的特点,首先在32×32变换单元中,根据已编码4×4系数组(CG)系数值的分布特性,自适应决定下一个CG的哥伦布-莱斯(Golomb-Rice)初始参数值;其次,在变换跳过模式系数块中设置初始Golomb-Rice参数为1,再利用相邻系数的相关性,根据已编码系数绝对值大小自适应决定下一系数的编码参数值.实验结果表明,与HEVC标准算法HM16.0相比,所提算法能达到0.09%~2.75%的比特率下降,平均有效率90%以上,且峰值信噪比(PSNR)无损失,编码时间平均只增加了0.08%.与代表文献相比,所提算法平均节省0.49%比特率,PSNR平均提高0.01 dB.