一种改进预测结构的多视点视频编码

多视点视频编码是视频编码的研究热点之一。针对联合多视点视频编码(Joint Multi-view Video Coding,JMVC)采用的分层B帧预测结构编码复杂度高,随机访问性能较差等缺点,提出了一种改进的预测结构。所提出的预测结构对B视点中以前一帧作为其时间参考的帧仅采用时间预测,对所有P视点的非关键帧均不进行视点间预测,有效地降低了计算复杂度,提高了随机访问性能。通过选取合适的I视点位置,以减少结构简化带来的编码效率损失。实验结果表明,与分层B帧预测结构相比,所提出的预测结构在保证编码效率损失不大的情况下,显著降低了平均编码时间。改进的预测结构也具有更好的随机访问性能。     

基于相关性分析的MVC比特分配算法

针对目前尚未深入研究多视点视频编码（Multi—view Video Coding,MVC）码率控制的问题,提出了一种基于相关性分析的多视点视频编码码率控制算法。该算法的核心是先根据视差预测和运动预测的结构关系,将所有图像分成6种类型的编码帧,并改进二项式率失真模型,然后根据多视点视频相关性分析在各个视点之间进行合理的码率分配,将码率控制分成4层结构进行多视点视频编码的码率控制。其中,帧层码率控制考虑分层B帧等因素分配码率,基本单元层码率控制根据宏块的内容复杂度采用不同的量化参数。实验结果表明该码率控制算法实际码率与目标码率平均误差能控制0．6％。     

基于H.264标准的多视点视频编码方案的研究

为研究一种新的高效的多视点视频编码方法,提高编码效率,并有效地提高视点间随机切换访问的能力,利用H.264中的新技术多参考帧、SP/SI帧、分层B帧编码等,根据时空预测编码结构的方法,提出了一种基于分层B帧并有利于视点间随机切换访问的多视点视频编码方案.实验结果表明,该方案在提高了编码效率的同时,在视点较多的情况下能够有效地提高视点间随机切换访问的能力.     

基于视差估计算法的多视点视频预测方案

多视点视频编码是立体视频的关键技术,视差估计是目前多视点视频编码中常用的方法之一.探讨了多视点视频编码中的视差估计算法原理,对当前应用视差估计算法的几种典型预测结构进行了深入分析,提出一种结合分级B图与视点相关性的多视点编码方案,该方案在H.264/AVC的编码模型JM下实现.实验表明,该方案在兼顾随机访问性能的同时,实现了较高的编码效率,尤其适合视点间相关性较高的运动图像序列.     

基于时空相关的H.264多参考帧快速选择算法

H.264/AVC视频编码标准采用的多参考帧技术改善了视频质量,但同时也增加了编码复杂度。为避免搜索多余的参考帧,提高H.264编码器的编码效率,基于视频序列帧间具有较强时间相关性、相邻宏块具有较强时空相关性,提出了一种多参考帧选择算法。该算法根据视频序列的帧间时间相关程度确定参考帧个数;由相邻宏块的时空相关性自适应确定当前宏块的编码模式及其最佳参考帧。实验结果表明,与校验模型JM16.2相比,该算法在编码质量几乎不变的情况下,平均可节约60%的编码时间。     

基于双目感知的多视点视频快速编码算法

为了减少多视点视频编码过程中多参考帧预测技术巨大的编码复杂度,提出基于双目恰可察觉失真(BJND)的多视点视频多参考帧快速选择算法,通过分析多参考帧选择与BJND之间的统计特性,提前结束多参考帧选择过程。当BJND大于阈值时,确定参考帧列表中时间或者视点上第一参考帧为最优参考帧。实验结果表明,所提出的快速算法在几乎不影响编码率失真性能的情况下,比多视点视频编码校验模型平均节约76%的编码时间。     

基于宏块多相关性的多视点视频编码方法

为降低多视点视频编码( MVC)中过高的计算量,提出基于宏块多相关性的多视点视频编码视间预测与Direct模式提前终止算法。分析MVC参考模型( JMVC)中时域预测和视间预测的特点及Direct模式的分布情况。基于当前宏块的时间和视点之间率失真代价的大小关系判断是否进行视间预测。利用先前已编码宏块的编码模式信息确定是否跳过Direct模式。实验结果表明,同JMVC的全搜索算法相比,该算法能降低编码的计算复杂度,平均可达75.62%,同时保持几乎相同的编码率失真性能。     

基于时/空相关性的H.264帧内预测算法

为了降低H.264编码复杂度,提出一种基于时空相关性的快速帧内预测算法。该算法充分利用视频序列的时间相关性,自适应地根据先前编码宏块对当前宏块进行预判,在Intra_4×4和Intra_16×16预测方式之间进行选择;对Intra_4×4预测方式,依据模式聚集特性,参考先前帧和当前帧已编码宏块的预测模式统计特征,确定当前4×4子块的候选模式。实验结果表明,该算法在保证信噪比和比特率几乎不变的情况下,编码时间减少约40%,提高了编码效率。     

一种宏块帧间预测模式的快速选择算法

人们对视频质量和内容的多样性要求越来越高,传统的二维(2D)图像/视频无法满足人们的需求,能够提供三维(3D)视觉的立体/多视点视频技术越来越受到学术界和工业界的重视。多视点视频编码技术已经成为当前视频研究领域的热点之一。与单视点视频相比,多视点视频可以更加生动地再现现实场景,给人们提供身临其境的感觉,与此同时,巨大的数据量成为制约其广泛应用的瓶颈。因此,如何提高多视点视频的压缩编码效率成为多视点视频编码技术的主要目标,其中,由HHI组织提出的JMVM编码方案采用了视点间预测和时域预测相结合的预测结构,取得了出色的编码效率,这种预测结构被JVT选为MVC的参考预测结构。然而,采用多视点视频(MVC)参考预测结构的JMVM方案的计算复杂度很高,为了能够有效地降低MVC的计算复杂度,该文提出了一种高效的MVC预测方法,主要从宏块预测模式快速选择来降低MVC的计算复杂度。该方法对帧间8×8预测模式,16×8、8×16预测模式进行了快速的选择。     

多模式3维视频形状编码

目的 具有立体感和高端真实感的3D视频正越来越受到学术界和产业界的关注和重视,未来在3D影视、机器视觉、远程医疗、军事航天等领域将有着广泛的应用前景。对象基3D视频是未来3D视频技术的重要发展趋势,其中高效形状编码是对象基3D视频应用中的关键问题。但现有形状编码方法主要针对图像和视频对象,面向3D视频的形状编码算法还很少。为此,基于对象基3D视频的应用需求,提出一种基于轮廓和链码表示的高效多模式3D视频形状编码方法。方法 对于给定的3D视频形状序列逐帧进行对象轮廓提取并预处理后,进行对象轮廓活动性分析,将形状图像分成帧内模式编码图像和帧间预测模式编码图像。对于帧内编码图像,基于轮廓内链码方向约束和线性特征进行高效编码。对于帧间编码图像,采用基于链码表示的轮廓基运动补偿预测、视差补偿预测、联合运动与视差补偿预测等多种模式进行编码,以充分利用视点内对象轮廓的帧间时域相关性和视点间对象轮廓的空域相关性,从而达到高效编码的目的。结果 实验仿真结果显示所提算法性能优于经典和现有的最新同类方法,压缩效率平均能提高9.3%到64.8%不等。结论 提出的多模式3D视频形状编码方法可以有效去除对象轮廓的帧间和视点间冗余,能够进行高效编码压缩,性能优于现有同类方法,可广泛应用于对象基编码、对象基检索、对象基内容分析与理解等。     

基于相关性分析的多模式多视点视频编码

多视点视频编码方法除需具有较高编码效率外,还必须支持视点或时间的随机访问、低延时编解码、视点可分级等性能.多视点视频信号的时间、视点间相关性随相机密度、光照、对象运动等因素不同而变化.文中提出基于多视点视频信号相关性分析的多模式多视点视频编码方法,改变传统单一预测模式的多视点编码结构,将多种性能优良的预测编码模式有机结合,根据多视点视频相关性分析灵活选择合适的预测编码模式,以获得优异的编码综合性能.实验结果表明,所提出的多模式多视点视频编码方法在保证高压缩效率的前提下,可进一步降低复杂度,提高随机访问性能.     

A low energy adaptive motion estimation hardware for H.264 multiview video coding

Multiview video coding (MVC) is the process of efficiently compressing stereo (two views) or multiview video signals. The improved compression efficiency achieved by H.264 MVC comes with a significant increase in computational complexity. Temporal prediction and inter-view prediction are the most computationally intensive parts of H.264 MVC. Therefore, in this paper, we propose novel techniques for reducing the amount of computations performed by temporal and inter-view predictions in H.264 MVC. The proposed techniques reduce the amount of computations performed by temporal and inter-view predictions significantly with very small PSNR loss and bit rate increase. We also propose a low energy adaptive H.264 MVC motion estimation hardware for implementing the temporal and inter-view predictions including the proposed computation reduction techniques. The proposed hardware is implemented in Verilog HDL and mapped to a Xilinx Virtex-6 FPGA. The FPGA implementation is capable of processing 30 × 8 = 240 frames per second (fps) of CIF (352 × 288) size eight view video sequence or 30 × 2 = 60 fps of VGA (640 × 480) size stereo (two views) video sequence. The proposed techniques reduce the energy consumption of this hardware significantly.     

Motion and disparity vectors early determination for texture video in 3D-HEVC

3D-HEVC is the state-of-the-art video coding standard for 3D video, and it is an extension of high efficiency video coding (HEVC) standard. Besides the original HEVC coding tools, 3D-HEVC adopts some advanced coding tools, such as disparity vector (DV), inter-view prediction and inter-component prediction. However, these advanced tools lead to extremely high encoding complexity at the same time, thus it cannot be well applied in real-time multimedia systems. In this paper, we propose a motion and disparity vectors early determination algorithm to reduce 3D-HEVC computational complexity. First, based on the statistical analyses, the spatial and temporal motion vector (MV) candidates are adaptively reduced for the prediction unit (PU) with the Merge mode. Then, for the PU with the Inter mode, the combination of spatial and temporal candidates is used to early determine the final MV. Finally, an adaptive optimization algorithm is adopted to select the valid inter-view disparity vectors (DV) candidates. Moreover, if the difference between candidate vectors is within a conditional range, current PU will be encoded with the Merge mode to skip unnecessary coding process. Experimental results show that for the texture views encoding, the proposed algorithm achieves an average of 33.03% encoding time saving, and an average of 0.47% BD-Rate increases.

     

基于小波变换的多视角视频可伸缩编码系统

构建基于离散小波的多视角编码系统。对多视角视频进行四维小波分解,包括一维时间分解、一维视角分解和二维空间分解。利用小波的多分辨特性和嵌入式编码器时间、空间、视角及质量可伸缩的特点,在一定带宽限制下,采用率失真优化的方法对各个子带的码率进行优化截断。实验结果表明,该编解码系统具有较好的视频重建图像质量。     

基于三维重建技术的多视角视频编码算法

对于多视角视频，尤其是多达几十路视频输入的全景多视角电视这一类应用，必须采取高效的编码方法来对海量的原始数据进行压缩和处理。本文提出了一种基于三维重建技术的全景多视角视频编码算法，三维重建技术的核心思想是基于由多幅二维图像来恢复空间物体三维信息。本算法包括了高效的对应基元匹配和预测编码算法，实现了利用先验空闻几何知识，参考同一时刻位于不同通道的两帧来对当前帧做出高效的预测，实验表明，本算法有效的降低了预测编码时的计算复杂度,提高了搜索速度。     

Long-term prediction for hierarchical-B-picture-based coding of video with repeated shots

The latest video coding standard High Efficiency Video Coding (HEVC) can achieve much higher coding efficiency than previous video coding standards. Particularly, by exploiting the hierarchical B-picture prediction structure, temporal redundancy among neighbor frames is eliminated remarkably well. In practice, videos available to consumers usually contain many repeated shots, such as TV series, movies, and talk shows. According to our observations, when these videos are encoded by HEVC with the hierarchical B-picture structure, the temporal correlation in each shot is well exploited. However, the long-term correlation between repeated shots has not been used. We propose a long-term prediction (LTP) scheme to use the long-term temporal correlation between correlated shots in a video. The long-term reference (LTR) frames of a source video are chosen by clustering similar shots and extracting the representative frames, and a modified hierarchical B-picture coding structure based on an LTR frame is introduced to support long-term temporal prediction. An adaptive quantization method is further designed for LTR frames to improve the overall video coding efficiency. Experimental results show that up to 22.86% coding gain can be achieved using the new coding scheme.     

Encoder-independent decoder-dependent depth-assisted error concealment algorithm for wireless 3D video communication

Three-Dimensional Multi-View Video (3D MVV) contains diverse video streams taken by different cameras around an object. Thence, it is an imperative assignment to fulfill efficient compression to attain future resource bonds whilst preserving a decisive reception MVV quality. The extensive 3D MVV encoding and transmission over mobile or Internet are vulnerable to packet losses on account of the existence of severe channel faults and restricted bandwidth. In this work, we propose a new Encoder-Independent Decoder-Dependent Depth-Assisted Error Concealment (EIDD-DAEC) algorithm. It invests the depth correlations between the temporally, spatially, and inter-view adjoining Macro-Blocks (MBs) to conceal the erroneous streams. At the encoder, the existing inter-view, temporal, and spatial matching are exploited to efficiently compress the 3D MVV streams and to estimate the Disparity Vectors (DVs) and Motion Vectors (MVs). At the decoder, the gathered MVs and DVs from the received coded streams are used to calculate additional depth-assisted MVs and DVs, which are afterwards combined with the collected candidate texture color MVs and DVs groups for concealing the lost MBs of inter- and intra-encoded frames. Finally, the optimum DVs and MVs concealment candidates are selected by the Directional Interpolation Error Concealment Algorithm (DIECA) and Decoder Motion Vector Estimation Algorithm (DMVEA), respectively. Experimental results on several standardized 3D MVV sequences verified the efficacy of the proposed EIDD-DAEC algorithm by achieving ameliorated efficacious objective and subjective results without generating and transporting depth maps at the encoder. The proposed work achieves high 3D MVV quality performance with an improved average Peak Signal-to-Noise Ratio (PSNR) gain by up to 0.95 ~ 2.70 dBs compared to the state-of-the-art error concealment algorithms, which do not employ depth-assisted correlations at different Quantization Parameters (QPs) and Packet Loss Rates (PLRs) of 40%.