Adaptive depth truncation filter for MVC based compressed depth image

In multiview video plus depth (MVD) format, virtual views are generated from decoded texture videos with corresponding decoded depth images through depth image based rendering (DIBR). 3DV-ATM is a reference model for the H.264/AVC based multiview video coding (MVC) and aims at achieving high coding efficiency for 3D video in MVD format. Depth images are first downsampled then coded by 3DV-ATM. However, sharp object boundary characteristic of depth images does not well match with the transform coding based nature of H.264/AVC in 3DV-ATM. Depth boundaries are often blurred with ringing artifacts in the decoded depth images that result in noticeable artifacts in synthesized virtual views. This paper presents a low complexity adaptive depth truncation filter to recover the sharp object boundaries of the depth images using adaptive block repositioning and expansion for increasing the depth values refinement accuracy. This new approach is very efficient and can avoid false depth boundary refinement when block boundaries lie around the depth edge regions and ensure sufficient information within the processing block for depth layers classification. Experimental results demonstrate that the sharp depth edges can be recovered using the proposed filter and boundary artifacts in the synthesized views can be removed. The proposed method can provide improvement up to 3.25 dB in the depth map enhancement and bitrate reduction of 3.06% in the synthesized views.     

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%。     

Edge-preserving Intra mode for efficient depth map coding based on H.264/AVC

Depth-image-based-rendering (DIBR) algorithms for 3D video communication systems based on the “multi-view video plus depth” format are very sensitive to the accuracy of depth information. Specifically, edge regions in the depth data should be preserved in the coding/decoding process to ensure good view synthesis performance, which directly affects the overall system performance. This paper proposes a novel scheme for edge-aware Intra depth compression based on the H.264/AVC framework enabled on both Intra (I) and Inter (P) slices. The proposed scheme includes a new Intra mode specifically targeted to depth macroblocks with arbitrarily shaped edges, which are typically not predicted well by the standard Intra modes of H.264/AVC and result in high rate–distortion costs. The proposed algorithm segments edge macroblocks into two regions each approximated by a flat surface. A binary mask identifying the two regions is defined and encoded by means of context-coding with adaptive template selection. As a novel contribution, the proposed mode allows exploiting the correlation with causal neighboring edge macroblocks to improve the performance of context-coding of binary masks and allow significant bit rate savings. The proposed method has been exhaustively compared with different state-of-the-art algorithms for edge-aware depth coding and the results highlight significant improvements in most of the cases, both in terms of reconstructed depth quality, view synthesis performance, and overall texture plus depth rate–distortion performance.     

An image feature-based method to efficiently determine inter-coding depth in HEVC

The quad-tree based picture partition scheme in High Efficiency Video Coding (HEVC) results in a more substantial increase in computational complexity than those incurred by its predecessor video coding standards because of the need in this scheme to determine the best coding unit (CU) partitions. In this paper, we propose a method to effectively reduce the computational complexity of inter-prediction coding in the HEVC standard. The relative displacement of the largest coding unit (LCU) at the corresponding position between adjacent frames is tested through optical flow (motion estimation). The texture intensity of the LCU at the given time is tested if the condition that determines the coding depth in advance cannot be satisfied. The depth of the coding unit (CU) can be determined in advance beyond the xCompressCU function by using our proposed method, which does not require the calculation of the rate-distortion (RD) cost for each level of depth, and thus reduces the circular traversal times of the xCompressCU function. Experimental results proved that our proposed method is effective, as it reduced the computational complexity of an encoder by 53.2% on average, and had a slight influence on coding performance.     

Object-based stereo video compression using fractals and shape-adaptive DCT

Based on the classical fractal video compression method, an improved object-based stereo video compression scheme with Shape-Adaptive DCT is proposed in this paper. Firstly, we use more effective macroblock partition scheme instead of classical quadtree partition scheme; thus reducing the block searching strategy. The stereo fractal video coding is proposed which matches the macroblock with two reference frames in left and right view results in increasing compression ratio and reducing bit rate when transmitting compressed stereo data. The stereo codec combines the Motion Compensation Prediction (MCP) and Disparity Compensation Prediction (DCP). Fractal coding is adopted and each object is encoded independently by a prior video segmentation alpha plane, which is defined exactly as in MPEG-4. The testing results with the nature monocular and stereo video sequences provide promising performances at low bit rate coding. We believe it will be a powerful and efficient technique for the object-based monocular and stereo video sequences coding.     

基于最大可容忍深度失真模型的低复杂度深度视频编码

在保证虚拟视点绘制质量的前提下,如何降低深 度视频的编码复杂度是一个亟需解决的问题。本文提出了一 种基于最大可容忍深度失真(MTDD,maximum tolerable d epth distortion)模型的低复杂度深度编码算法,将MTDD模型引 入 到率失真(RD)代价函数,通过对编码单元(CU)进行失真度量判决 ,如果对当前CU进 行编码不会导致可察觉的绘制失真,则失真度量只考虑深度编码失真,否则失真度量同时考 虑深度编码失真和视点 合成失真(VSD),从而降低编码复杂度。实验结果表明,所 提出的算法在不 降低虚拟视点绘制质量和不增加编码码率的情况下,能显著降低深度视频的编码复杂度。     

H.264并行视频编码的分配机制的研究

H.264作为新的视频压缩标准,采用了许多先进的算法,提供了很好的视频压缩质量。获得出色压缩效果和质量的代价是压缩编码算法复杂度的增加。为了寻求更高的编码速度,集群并行计算被运用到H.264的视频编码计算中。本文结合并行算法设计,通过对H.264视频编码的研究,分析了H.264可实现并行计算的任务单元选择;采用了片（Slice）级的H.264并行编码计算方法,并对其性能进行了测试和分析。     

基于H.264的FGS视频编码及其在视频会议系统中的应用

主要介绍视频会议系统的基本概念及其对视频编解码技术提出的要求,在MPEG-4精细可伸缩性编码(FGS)的基础上,提出了一种基于H.264的精细可伸缩性视频编码方案,仿真和实验结果表明,基于H.264的FGS具有更高的信噪比和视觉质量,能较好地满足基于IP的H.323视频会议系统不同终端的视频质量要求。     

一种适用于H.264/AVC的自适应码率控制算法

码率控制在视频编码中起着非常重要的作用。根据H.264/AVC编码标准的特性及其HDR部分对码率控制的要求,文章采用一种适用于H.264/AVC的自适应码率控制算法,该算法实现了率失真优化与码率控制的结合,保证了编解码缓冲区既不上溢又不下溢。实验结果表明,与早期JVT提案中的码率控制方法相比,本文所采用的方法能够在准确控制码率的同时提高视频序列的PSNR值。     

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BF561的H.264并行编码的研究

基于H.264视频编码标准和多核DSP ADSP-BF561的结构特点,提出了一种H.264并行编码方案.这种方案将输入视频分为两个相对独立的Slice编码,适应该DSP的同构双核结构,充分发挥了DSP的处理性能.实验结果表明,该并行方案在几乎不降低图像质量的情况下,编码速度提高了40%左右.     

Efficient Inter Prediction Mode Decision Method for Fast Motion Estimation in High Efficiency Video Coding

High Efficiency Video Coding (HEVC) is the most recent video coding standard to achieve a higher coding performance than the previous H.264/AVC. In order to accomplish this improved coding performance, HEVC adopted several advanced coding tools; however, these cause heavy computational complexity. Similar to previous video coding standards, motion estimation (ME) of HEVC requires the most computational complexity; this is because ME is conducted for three inter prediction modes — namely, uniprediction in list 0, uniprediction in list 1, and biprediction. In this paper, we propose an efficient inter prediction mode (EIPM) decision method to reduce the complexity of ME. The proposed EIPM method computes the priority of all inter prediction modes and performs ME only on a selected inter prediction mode. Experimental results show that the proposed method reduces computational complexity arising from ME by up to 51.76% and achieves near similar coding performance compared to HEVC test model version 10.1.     

一种基于对象的分形视频压缩算法研究

基于分形视频压缩的典型方法,提出了一种改进并提高其压缩性能的方法,用更有效的宏块划分规则替代传统的四叉树划分规则、简化块的搜索策略和范围、使用类似H.264标准的I帧和减少重复计算等。提出了一种在分形视频压缩算法中的基于对象(OB)压缩的实现方法,可以对任意对象单独进行压缩编码,极大地提高压缩比和压缩速度,降低比特率并节省数据传输时的带宽。实验结果表明,相比典型的方法,本文提出的分形视频压缩算法,压缩比提高了近4倍,压缩速度快近10倍,图像质量提高了3～5dB,显著地提高了分形视频压缩算法的性能;同时,OB的压缩方法简单有效,压缩比和压缩速度又有大幅度提高,使分形视频压缩的应用具有更大的灵活性和实用性。     

新一代运动图像压缩标准H.264/AVC

H.264/AVC是ISO/IECMPEG与ITU-TVCEG共同制订的新一代图像编码标准,它具有更高的压缩性能。文章介绍H.264/AVC图像编解码系统的实现过程,并对其采用的新技术进行描述。     

Encoder adaptable difference detection for low power video compression in surveillance system

As a state-of-the-art video compression technique, H.264/AVC has been deployed in many surveillance cameras to improve the compression efficiency. However, it induces very high coding complexity, and thus high power consumption. In this paper, a difference detection algorithm is proposed to reduce the computational complexity and power consumption in surveillance video compression by automatically distributing the video data to different modules of the video encoder according to their content similarity features. Without any requirement in changing the encoder hardware, the proposed algorithm provides high adaptability to be integrated into the existing H.264 video encoders. An average of over 82% of overall encoding complexity can be reduced regardless of whether or not the H.264 encoder itself has employed fast algorithms. No loss is observed in both subjective and objective video quality.     

基于图像分割的深度视频校正算法

在基于深度图的虚拟视点绘制过程中,由于通过深 度估计软件获取的深度视频存在大量的失真,从而导致绘制的虚拟视点中存在纹理失真和缺 失现象。本文围绕深度视频失真类型,提出一种基于分割的深度 视频校正算法。利用彩色深度一致性信息分区域校正深度失真,以解决由于深度块失真造成 的虚拟视点纹理 缺失问题。首先,提取彩色视频运动和边缘区域,得到彩色视频边缘和运动区域掩模图;其 次,在边缘和运 动信息的辅助下,对彩色图像进行Mean Shift聚类,并将不同类别区域赋以不同的标签;最 后,分别统计不 同类别连通区域对应的深度直方图,利用其峰值校正深度视频中深度彩色非一致区域。实验 结果表明,本文提 出的基于分割块的深度视频校正算法优于部分基于像素的滤波算法,可以有效地校正深度视 频块失真,解决 虚拟视点边缘失真和纹理缺失问题,同时虚拟视点质量平均提高了0.20dB。     

H.264视频压缩关键技术及其应用前景

ISO/IEC和ITU-T联合制定的H.264标准,标志着视频压缩技术的最新进展.H.264视频编码新标准采用一系列最新的压缩技术,提高了压缩率.该文重点介绍了视频编码新标准H.264的关键模块,并阐述了它在数字电视、高清晰度电视以及移动通信等方面的应用前景.     

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.     

基于H.264/SVC的视频加密技术研究

随着网络的不断普及和发展,视频数据在网络中有了越来越多的应用,随之也提出了视频安全的问题,通过视频加密可以很好地解决此问题。文中分析了目前主流的H.264SVC标准所采用的可分级视频编码技术,根据视频分级编码特点选取关键信息进行分层加密,实现不同级别的视频加密。同时,所提方案采用了序列密码进行加密,具有较高的安全性。试验结果表明:该方案具有安全性高、复杂度适中、实时性好等特点。