波形内插语音编码器中快渐变波形幅度的量化

在低速率参数语音编码算法中,如何用有限的比特数有效地量化幅度谱是一个关键问题。本文对波形内插语音编码模型中快渐变波形幅度的量化问题进行了深入研究和分析,提出了一种基于矢量变维和DCT的REW幅度感觉加权量化方案,该方法降低了编码比特数,减少了存储和计算复杂度,增强了编码语音的感性质量。主观听力测试结果表明该量化方案在每帧4比特时的WI语音编解码质量要优于用基于DCT的REW幅度矩阵量化方案在每帧10比特时的重建语音质量。     

基于图像特征的视频编码码率控制策略

根据缓存器的状态和信道速率，为待编码帧在图像层上预分配目的编码比特数，并使用小波变换系数来表征图像特性，继而为帧内每一具体宏块选定量化因子，提出了基于图像特征的码率控制策略。仿真结果表明，该码率控制策略能有效地避免缓存器出现上、下溢的情况，并使输出码率趋于稳定。     

基于最佳量化的序列图像编码转换码率控制策略

该文分析了编码转换缓冲区的状态,导出了编码转换缓冲区为防止解码器缓冲区下溢和上溢应满足的条件,建立了序列图像编码转换模型。并根据编码转换缓冲器的状态和信道速率,为待编码帧在图像层上预分配目的序列图像编码比特数,使用DCT系数分布特性来表征图像特性。继而为帧内每一具体宏块选定最佳量化因子,提出了基于最佳量化的码率控制策略,模拟实验表明,该码率控制策略能有效地减少、避免缓冲区出现上、下溢的情况,使输出码率趋于稳定,提高了重建序列图像的信噪比。     

H.263活动图像编码器码率控制研究

本文分别在图像层和宏块层进行 Ｈ２６３ 的码率控制。在图像层采用后向自适应控制的方法,通过引入量化步长因子—编码输出比特数映射表,确定每帧图像量化步长因子的基准值。在宏块层采用前向控制的方法,根据视觉掩蔽特性设计模糊分类器,确定人眼对每个宏块的敏感程度和相应的量化步长因子。能在视频输出码率恒定的条件下,保持图像质量的稳定,取得较好的视觉效果。     

宽带ISF参数的非等系数帧间预测分裂矢量量化方法

 本文提出了一种新的适用于宽带语音编码ISF参数量化的非等系数帧间预测分裂矢量量化方案.该量化方案利用ISF参数的帧间相关性,基于预测分裂矢量量化原理,首先对待量化的ISF参数矢量进行去均值和非等系数帧间预测,然后对去均值后的ISF参数的预测残差进行分裂矢量量化.实验表明,该算法在每帧编码比特数为46bits时达到了透明量化,且平均谱失真比G.722.2中ISF参数量化的平均谱失真小.     

移动无线互联网接入中视频编码率控制策略

建立了用于移动无线互联网接入的视频编码转换模型,提出了自适应运动矢量估值方法.将编码转换码率控制分为图像层控制和宏块层两级,首先在总体上对每帧图像的编码比特数进行预分配,然后采用小波变换系数来表征图像特征,为帧内不同特征的宏块选用不同的量化因子,提出了一种新的码率控制策略.模拟实验表明:该方法在视频图像质量没有明显失真的前提下,提高了视频编码转换速度;编码转换输出码流和编码转换缓冲区占用量较稳定,重建图像的信噪比得到了明显的改善.     

多次观测信号检测的最优量化

信号检测的最优量化是降低实现复杂度的重要手段.在有限精度量化前提下,本文推导了多次观测信号检测的检测性能(检测概率和虚警概率),并证明了实际信号环境中多次观测积累值是最佳统计量.文中进一步提出了基于遗传算法的最优量化设计方法,可方便地优化等效检测能力因子等各种检测性能指标,离线设计最优量化参数.以红外弱小目标检测多帧图像预积累为例,最优量化设计可将量化比特数由通常的8~14比特减少到2~4比特,有效降低图像处理实现复杂度.     

一种改进的H.264/AVC帧层码率控制算法

针对JVT-G012算法在帧层对P帧目标比特分配太过均匀,忽略了图像复杂度的问题,提出了一种简单有效的帧差比值法来进行帧层目标比特的分配,并利用缓冲区充盈度来调整当前帧量化参数的方法.通过大量实验仿真表明,与JVT-G012算法相比,该算法不仅能够更精确地控制码率,而且还提高了视频图像的质量.     

灰度分布基于规范式描述的边缘模型基图像编码

提出了一种称为边缘模型基的低比特率图像编码方法,其基本特点是：1）建立一种基于图像边缘信息的活动图像信源模型,按照图像中物体的结构将图像划分为激励区和缓变区（平滑区）。2）用三阶规范式拟合图像激励区的灰度分布,以“激程扫描─规范式拟合”表达图像的缓变区。3）引入了模型匹配与广义运动分析概念,并用干帧间图像预测编码。实验结果表明：在保持重建图像质量的前提下,每像素的比特数可压缩至0.075。     

基于神经网络的视频编码量化参数选择算法

提出了一种基于神经网络的视频量化参数选择,利用已编码帧信息对当前帧的量化参数计算进行调整.神经网络模型选取当前帧的目标比特、当前帧的MAD和前一帧编码的QP和实际比特数作为输入,输出值经过反归一化及取整处理对视频进行量化.实验在H.264/AVC的标准参考软件JM14.2中实现,编码时使用该方法在保证码率精确度和平均PSNR值基本不变的情况下,减小了PSNR的波动.     

A new rate control scheme for H.263 video transmission

In some image/video applications, the variable bit rate image/video bitstream will be transmitted over a constant bit rate transmission channel, in which a channel buffer is employed. In this study, a new rate control scheme for H.263 video transmission is proposed. Three proposed techniques include: preprocessing the INTRA coded macroblock (MB) incorporated the just-noticeable-distortion (JND) concept, constructing a bit estimation model in the frequency domain (instead of the bit estimation model in the spatial domain employed in Test Model Near-term version 11 (TMN11)), and adjusting quantization parameter (QP) for each MB by a Lagrangian optimization strategy.In the proposed approach, the target number of bits for a video frame is first obtained by using a simple rate control procedure for the frame layer. The proposed JND preprocessing is applied on all the INTRA coded MBs so that the number of coded bits for a scene changed frame will decrease, without any perceptual loss. Within the MB layer, instead of the bit estimation model in the spatial domain employed in TMN11, a bit estimation model in the frequency domain, directly depending on discrete cosine transform coefficients, is proposed. Then the Lagrange multiplier is used to determine the optimal QP for each MB. The resulting QP and number of coded bits of the current MB are fed backward to update the parameters of the bit estimation model.Based on the simulation results obtained in this study, the proposed approach can meet the target bit rate more accurately, keep a lower channel buffer fullness (delay), and have a larger average frame rate than TMN11, whereas the peak signal-to-noise ratio value and the processing time of the proposed approach are “approximately” as good as that of TMN11.     

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.     

Human centered perceptual adaptation for video coding

Traditional visual saliency based video compression methods try to encode the image with higher quality in the region of saliency. However, the saliency feature changes according to persons, viewpoints, and distances. In this paper, we propose to apply a technique of human centered perceptual computation to improve video coding in the region of human centered perception. To detect the region of interest (ROI) of human body, upper body, frontal face, and profile face, we construct Harr and histogram of oriented gradients features based combo of detectors to analyze a video in the first frame (intra-frame). From the second frame (inter-frame) onward, the optical flow image is computed in the ROI area of the first frame. The optical flow in human centered ROI is then used for macroblock (MB) quantization adjustment in H.264/AVC. For each MB, the quantization parameter (QP) is optimized with density value of optical flow image. The QP optimization process is based on a MB mapping model, which can be calculated by an inverse of the inverse tangent function. The Lagrange multiplier in the rate distortion optimization is also adapted so that the MB distortion at human centered region is minimized. We apply our technique to the H.264 video encoder to improve coding visual quality. By evaluating our scheme with the H.264 reference software, our results show that the proposed algorithm can improve the visual quality of ROI by about 1.01 dB while preserving coding efficiency.     

一种改进的基于柯西模型的H.264码率控制方法

H.264/AVC编码中的码率控制是通过有效控制输出码流的码率来提高其压缩视频质量的重要技术。本文基于H.264/AVC中的JVT-H017码率控制方案提出了一种改进算法。新算法根据H.264中DCT系数的分布特征,将柯西分布引入到码率控制模块,用更精确的柯西率失真模型取代了原先的二次率失真模型。在此基础上,进一步引入了一种联合PSNR比率和MAD比率进行图像复杂度预测的方法,并依此来调整帧级比特的分配和量化参数,克服了在出现复杂运动或场景切换时,因视频序列相邻帧之间相关性降低而导致的MAD预测失准的情况。实验结果表明,与JVT-H017方案及文献[5]中的算法比较,新的算法不仅具有更精确的码率控制,而且明显改善了输出码率的平稳性及重建图像的PSNR。      

多版本备份和限制性双重认证主密钥(t,s,k,n)图像分存

传统影子图像连接的（t,s,k,n）分存易导致分发影子图像大小不等,基于伯克霍夫插值的（t,s,k,n）分存不能高效恢复;而双认证自修复图像分存对密图和备份图恢复能力十分有限.针对以上问题,采用随机参与值通过（k,s）和（k-t,n-s）分存来构造主密钥（t,s,k,n）分存并通过第3方公信方存储的MD5值以防止作弊.所提策略由主密钥对密图LL子带置乱来形成对显著比特多备份、对非显著比特少备份和经主密钥不同程度置乱的多版本备份图;引入限制性双重认证在保持认证精度的同时,将尽可能多的备份比特通过GF（2^8）域（k,n）分存嵌入来形成嵌密掩体.理论和实验表明,主密钥（t,s,k,n）分存可高效求解;随机参与值可避免参与者编号泄露,分发信息的篡改和认证比特的揣测;多版本备份可对备份图高置信度地恢复;而限制性双重认证在认证能力上不低于双认证自修复图像分存.     

Motion adaptive video coding scheme for time‐varying network

Adaptive video coding algorithms can encode a video stream dynamically on the basis of the amount of bandwidth available in a network. In this paper, a novel approach for adaptive video coding based on look‐up tables has been proposed. On the basis of the network conditions, the proposed codec estimates quantization parameter (QP) and also the spatial resolution for a group of pictures from the look‐up table. Then, QP for each frame is estimated on the basis of the motion content in each frame. More motion leads to more burden of bits while encoding the motion vectors. Also, quantization noise is less prominent in high‐motioned frames than frames possessing low motion information because of the temporal masking phenomenon of the human eyes. So, the main trick of the proposed scheme is to assign higher QP to the frames having higher motion than those having less motion. This method also reduces the requirement of excess bits for encoding of motion vectors having higher motion content. Additionally, QP is adjusted on the basis of the buffer availability in order to avoid bit loss error. Experimental results show the efficacy of the proposed codec. Copyright © 2013 John Wiley & Sons, Ltd.     

一种面向HEVC的并行码率控制算法

视频通信时通常带宽有限,为了能在规定的目标码率下获得尽可能高质量的解码图像,需要在视频编码时进行码率控制.目前针对HEVC的并行编码以及对应码率控制已成为研究热点,现有并行结构下的平均比特率控制算法受到帧间依赖性的约束,待编码帧无法及时获得与其并行编码帧的实际比特数,因此本文算法通过预测并行帧的实际比特数来进行码率控制,并在此基础提出了自适应调整帧层量化参数补偿值.仿真结果表明,相比已有算法,前者减少码率误差约为3.38％,后者可提高PSNR约为0.204 dB同时减少约0.3％的码率误差.     

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。     

低码率下基于ROI与JND的分级量化方法

传统基于人眼感兴趣区域(ROI)的分级量化模型,将视频帧划分为ROI区域和非ROI区域,对相应区域用不同的量化参数(QP)进行量化,以提升视频的主观质量.而该模型没有考虑ROI区域的内部特性,不能很好地符合人眼视觉特性(HVS).针对低码率条件下以人脸为主体的桌面视频、手持终端等场景,提出一种基于ROI和恰可观测失真(JND)的分级量化方法.JND模型表明边界区域相对平滑区域能够隐藏更多的失真,利用该属性检测出ROI区域(即人脸)中人眼更感兴趣的边界部分(例如眼睛、鼻子、嘴巴等),据此建立基于ROI与JND的分级量化模型,指导各区域的量化.实验结果表明,针对低码率视频的应用,与传统分级量化方法相比,本文所提方法在相同码率条件下能明显提升视频的主观质量.