新一代基于HEVC的3D视频编码技术

HEVC标准出台后,新一代基于HEVC的多视点加深度编码也将正式推出。基于HEVC的3D视频编码作为HEVC标准的扩展部分,主要面向立体电视和自由立体视频。从该编码方式的基本结构出发,较全面地介绍了视频编码方式、深度图编码方式和对深度图的编码控制三个方面的关键技术,包括视点间运动预测、深度图建模模式和视点合成优化等技术。     

采用灰度共生矩阵进行深度预判的3D-HEVC深度图帧内快速编码算法

针对3D视频的3D-HEVC编码标准以多视点纹理视频和深度视频格式进行编码,其深度图编码仍延续纹理视频编码的模式和编码尺寸遍历选择,使得3D-HEVC的编码复杂度居高不下。本文针对深度图帧内预测编码,采用灰度共生矩阵对深度图中的CTU进行计算,统计并分析其矩阵中非零值个数与CTU分割深度的关系,根据非零值个数分布规律,设定阈值,使得帧内编码时可以预判编码模块的分割深度,从而选择性跳过部分不同深度CU的帧内预测过程。经过HTM16.0测试平台的检验,本算法在全帧内编码模式下,测试序列合成视点比特率仅增加0.08%的同时,平均节省了16.8%的编码时间,与其他同类较新算法在HTM16.0平台上的性能比较也有一定的优势。      

3D电视系统的构成及发展

主要介绍了3D电视系统的现状与发展,按照由双视点向未来多视点3D电视系统发展的技术路线,依次介绍了各阶段系统的架构.同时,对关键技术的基本原理也做了详细说明,包括过度阶段的帧兼容、多视点视频编码、混合分辨率视频编码、视频与相应深度信息联合编码等解决方案.最后对3D电视系统中有待解决的问题和未来的研究方向进行了总结.     

结合预处理的深度视频帧内快速编码算法

多视点彩色加深度(MVD)视频是三维(3D)视频的 主流格式。在3D高效视频编码中,深度视频帧内编码 具有较高的编码复杂度;深度估计软件获取的深度视频由于不够准确会使深度图平坦 区域纹理增加, 从而进一步增加帧内编码复杂度。针对以上问题,本文提出了一种联合深度处理的深度视频 帧内低复杂度 编码算法。首先,在编码前对深度视频进行预处理,减少由于深度图不准确而出现的纹理信 息;其次,运 用反向传播神经网络(BPNN,backpropagation neural network)预测最大编码单元 (LCU,la rgest coding unit)的最大划分深度;最后联合深度视频的边缘信 息及对应的彩色LCU最大划分深度进行CU提前终止划分和快速模式选取。实验结果表明, 本文算法在保证 虚拟视点质量的前提下,BDBR下降0.33% ,深度视频编码时间平均节省50.63%。     

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。     

基于纹理平滑度的视点合成失真优化快速算法

针对3D-HEVC中深度图编码采用的视点合成失真优化方法的高复杂度问题,提出一种基于纹理平滑度的快速算法。首先结合帧内DC预测特性和统计学方法分析平坦纹理图中像素规律并设定基于纹理图平坦度的跳过准则;然后在深度图编码采用视点合成失真优化方法时提前分离出纹理图平坦区域所对应的深度图区域,并终止该区域像素基于虚拟视点合成的视点合成失真计算过程。实验结果证明该算法的有效性,能在保持编码质量的同时减少大量编码时间。     

基于多分支网络的深度图帧内编码单元快速划分算法

3维高效视频编码(3D-HEVC)标准是最新的3维(3D)视频编码标准,但由于其引入深度图编码技术导致编码复杂度大幅增加。其中,深度图帧内编码单元(CU)的四叉树划分占3D-HEVC编码复杂度的90%以上。对此,在3D-HEVC深度图帧内编码模式下,针对CU四叉树划分复杂度高的问题,该文提出一种基于深度学习的CU划分结构快速预测方案。首先,构建学习深度图CU划分结构信息的数据集;其次,搭建预测CU划分结构的多分支卷积神经网络(MB-CNN)模型,并利用构建的数据集训练MB-CNN模型;最后,将MB-CNN模型嵌入3D-HEVC的测试平台,通过直接预测深度图帧内编码模式下CU的划分结构来降低CU划分复杂度。与标准算法相比,编码复杂度平均降低了37.4%。实验结果表明,在不影响合成视点质量的前提下,该文所提算法有效地降低了3D-HEVC的编码复杂度。     

纹理-深度图共同优化的3D-HEVC帧内快速算法

随着立体及3D视频需求的日益增多,针对3D视频编码方法的研究受到越来越多的关注。3D-HEVC编码标准对采用纹理和深度图格式融合的3D视频进行编码,由于加入了深度图编码,因此新增了深度图编码模式、组件间预测和分段直流编码等技术,使其编码复杂度急剧升高。为了减少3D-HEVC的编码时间,本文提出了针对纹理图和深度图的编码单元（Coding Unit, CU）尺寸提前决策快速算法。利用梯度矩阵和作为当前CU和子CU复杂度的判断依据,将CU分为三类:不划分CU（Non-Split Coding Unit, NSCU）、直接划分CU（Split Coding Unit, SCU）以及普通CU。对NSCU,跳过小尺寸的帧内预测过程;对SCU,直接跳过当前CU的帧内预测过程;对普通CU,执行原平台操作。实验结果表明,与原始平台相比,本文算法在合成视点质量基本不变的情况下,平均减少40.92%的编码时间;与最新的联合纹理-深度图优化的3D-HEVC快速算法相比,可以在质量相当的情况下减少更多的编码时间。      

面向三维高效视频编码的深度图错误隐藏

基于多视点视频序列视点内、视点间存在的相关性,并结合视点间运动矢量共享技术,该文提出一种面向3维高效视频编码中深度序列传输丢包的错误隐藏算法。首先,根据3D高效视频编码(3D-HEVC)的分层B帧预测(HBP)结构和深度图纹理特征,将深度图丢失块分成运动块和静止块;然后,对于受损运动块,使用结合纹理结构的外边界匹配准则来选择相对最优的运动/视差矢量进行基于位移矢量补偿的错误掩盖,而对受损静止块采用参考帧直接拷贝进行快速错误隐藏;最后,使用参考帧拆分重组来获取新的运动/视差补偿块对修复质量较差的重建块进行质量提升。实验结果表明:相较于近年提出的对比算法,该文算法隐藏后的深度帧平均峰值信噪比(PSNR)能提升0.25～2.03 dB,结构相似度测量值(SSIM)能提升0.001～0.006,且修复区域的主观视觉质量与原始深度图更接近。     

3D-HEVC深度图帧内编码快速算法

编码3D视频的3D-HEVC编码标准采用多视点加深度图的编码格式,新增的深度信息使编码复杂度剧增。本文针对编码块(Coding Unit,CU)的四叉树分割模型和帧内预测模式,提出了深度图帧内编码的快速算法。用Otsu’s算子计算当前CU的最大类间方差值,判断当前CU是否平坦,对平坦CU终止四叉树分割和减少帧内模式的遍历数目。根据子CU与上一层CU的相似性,利用已编码的上一层CU对提前终止CU分割算法做优化。本算法与原始3D-HEVC算法相比减少40.1%的编码时间,而合成视点的质量几乎无变化。      

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.     

Fast intra mode decision for depth coding in 3D-HEVC

The emergent 3D High Efficiency Video Coding (3D-HEVC) is an extension of the High Efficiency Video Coding (HEVC) standard for the compression of the multi-view texture videos plus depth maps format. Since depth maps have different statistical properties compared to texture video, various new intra tools have been added to 3D-HEVC depth coding. In current 3D-HEVC, new intra tools are utilized together with the conventional HEVC intra prediction modes for depth coding. This technique achieves the highest possible coding efficiency, but leads to an extremely high computational complexity which limits 3D-HEVC from practical applications. In this paper, we propose a fast intra mode decision algorithm for depth coding in 3D-HEVC. The basic idea of the proposed algorithm is to utilize the depth map characteristics to predict the current depth prediction mode and skip some specific depth intra modes rarely used in 3D-HEVC depth coding. Based on this analysis, two fast intra mode decision strategies are proposed including reduction of the number of conventional intra prediction modes, and simplification of depth modeling modes (DMMs). Experimental results demonstrate that the proposed algorithm can save 30 % coding runtime on average while maintaining almost the same rate-distortion (RD) performance as the original 3D-HEVC encoder.     

High-performance depth map coding for 3D-AVC

Achieving high-performance coding for a depth map is one of the most important challenges in 3D video coding. In this paper, a quality enhancement method is proposed to accomplish better coding efficiency. A new technique separating contour and flat regions is designed, and a contour-aware quality enhancement algorithm is presented to improve depth map quality. We also propose a fast mode decision process to reduce computational complexity. The proposed fast algorithm uses similarity between texture video and depth map coding. The encoding process for a depth map is terminated early by using coded information from a texture video. Experimental results show that the quality of the depth map is improved by 0.11–0.59 dB, which translates into a bit rate saving of 2.19–8.19 %. The proposed fast algorithm saves encoding time, on average, by 36.4 %.     

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.     

一种用于深度图编码的虚拟视失真估计模型

多视视频加深度(MVD,multi-view video plus depth)的3D视频格式中,深度图提供视频的场景几何信息,其不在终端成像显示而是通过基于深度图像的绘制(DIBR)技术用于绘制虚拟视图像。在深度图的压缩编码过程中,深度图的失真会引起绘制的虚拟视图像的失真。深度图用于绘制而不用于显示的特性使得准确估计深度图绘制的虚拟视失真可以提高深度图编码的率失真性能。本文分析了不同的深度图失真引起的不同的虚拟视失真,进而提出一种估计深度图失真引起虚拟视失真的指数模型,并将模型用于深度图编码的率失真优化(RDO)中。实验结果表明,本文提出的模型可以准确估计深度图失真引起的虚拟视失真,提高深度图编码性能,相比于HTM的VSO可以降低约10%的编码时间,并且虚拟视质量略优于HTM。     

Unified depth intra coding for 3D video extension of HEVC

With the development of high-efficiency video coding (HEVC), the newest video coding standard, 3D video extension of HEVC (3D-HEVC) has been actively investigated. Since 3D-HEVC uses multi-view texture and depth data for input, various coding tools have been added to HEVC. In 3D-HEVC, on top of the existing 35 HEVC intra modes, eight additional modes exist, which are specifically for depth coding. In this paper, we propose a unified depth intra coding method that incorporates such depth intra modes into the regular intra mode set. In particular, the most rarely used HEVC intra modes are replaced by depth intra modes. As a result, binarization for depth intra modes is removed. Furthermore, the most probable mode selection procedure is modified to consider the elimination of several angular intra modes. The proposed method is implemented and tested on 3D video HEVC test model version 7.0. Simulation results report 2.2 % synthesis gain under all-intra configuration.