基于线性预测的半像素运动估计

在视频编码系统中,半像素精度的运动估计虽可以明显地改善编码效果,但也因此增加了不少运算量。为了降低运算量和提高半像素运动估计的速度,提出了一种全新的半像素搜索算法(half-pixel motion estimation based on linear prediction,简称BLPHME),其关键思想是通过分析整像素搜索和半像素搜索结果之间的相关性来建立一个线性模型,通过动态调整判决门限,以便预测并跳过那些不能从半像素块匹配搜索中得到好处的块。实验结果表明,该算法不仅可以明显地降低运动估计的运算量,同时还能得到与传统算法非常接近的图像质量和码率。此外,该算法还可以和基于整像素和半像素的快速运动估计算法一起使用,以进一步降低运算量。     

一种新的H.264视频场景切换检测算法

H.264/AVC QCIF视频场景切换检测是视频应用中一个极具挑战性的研究课题,只利用宏块信息很难得到满意的检测效果,为此提出了一种采用动态阈值和AC相似度的H.264/AVC视频场景切换检测算法,考虑编码预测模式和DCT系数等信息,提出基于编码比特数的动态阈值和基于AC能量的AC图像相似性两个判决准则,据此进行视频场景切换检测。实验结果表明,在高速运动及场景切换频繁的视频上场景切换检测率得到提高,性能也优于现有的算法。     

道路交通场景监控视频编码研究

道路交通监控摄像机所能拍摄的最大场景范围已知,分析监控视频中交通流流动的规律,提出基于场景的压缩方法。通过运动在空间上的分布,建立运动能量图,取反获取掩模。改进HEVC编码方法,针对运动分布区域交通流的方向性强且运动剧烈特征,使用非对称模板改进TZSearch运动搜索算法;针对掩模区域运动性弱特征,提前设置运动搜索终止阈值。实验结果表明,与AVS2和MPEG-4编码相比,改进方法能够同时保证交通显著性以及压缩性能;与HEVC编码比较,改进方法的平均比特率节约、平均PSNR增效和平均时间节约分别为11.80%、3.90 dB和5.55%,车辆识别的准确率能够提高7.41%,增强了视频编码效率的同时强化了视频本身的分析性能。     

Region-based rate control and bit allocation for wireless video transmission

In this paper, we propose a joint source-channel region-based rate control algorithm for real-time video transmissions over wireless systems. During the video transmission, the channel throughput available to the video encoder in the wireless systems is inherently variable, due to the retransmission of the error packets using the automatic repeat request (ARQ) error control. The variable data rate of the wireless system is characterized by the packet-level Gilbert two-state Markov Model, the parameters of which are extracted from the statistical properties of the channel information obtained from the wireless channel simulator. The proposed algorithm adopts a fast but effective block-based segmentation method to extract the regions of interest. Unlike traditional bit allocation methods used in the region/content-based rate control, the algorithm exploits the most effective criteria "coding qualities" as quantitative factors to directly control bit allocation among different regions so as to achieve better visual quality in the regions of interest. The computational complexity of the algorithm is low making it suitable for real-time applications. Compared with the MPEG-4 rate control algorithm, our algorithm can effectively enhance the perceptual quality for the regions of interest and significantly reduce the number of frame skipping; thereby, improve the smoothness of the video.     

基于区域划分的深度视频快速编码算法

多视点彩色视频与深度视频作为多媒体系统中主流3D场景表示方式,吸引了越来越多人的关注。深度视频反映场景的几何信息,如何对其进行快速编码尤为重要。提出了一种基于区域划分的深度视频快速编码算法。首先,根据深度视频的边缘和运动属性把深度视频分为四个区域;然后,深入分析不同区域内宏块模式分布比例以及参考帧选择特性,设计了不同的宏块模式选择和参考帧搜索策略来提高编码速度;最后,测试提出算法的编码时间、码率以及合成虚拟视点的质量。实验结果表明,提出算法在保证虚拟视点图像质量和编码码率基本不变的情况下,节约了85.73%～91.06%的编码时间。     

基于CPLD芯片的视频图像码率控制方法研究

针对小波视频码率控制方法缓冲器容量有限,存在控制精准误差大的问题,提出了基于CPLD芯片的视频图像码率控制方法研究。依据基于CPLD芯片的视频图像码率控制框图可知,该码率控制方法是由CPLD芯片视频图像灰度增强、编码码率控制、视频质量控制与主动跳帧控制四个模块组成的。运用Philips公司的9位视频输入处理器sAA7113芯片解码视频,输出达到ITU656标准的YUV 4：2：2格式的数字视频信号。统一视频信号格式,利用灰度的线性变换的方式增强图像灰度,借助Verilog HDL描述CPLD执行算法。依据固定编码比特率和固定图像质量之间关系,获取编码特性,并计算缓冲区和编码帧目标比特数,依据当前渲染到纹理值,统计报文丢失率,由此实现视频图像编码码率控制。为了扩充缓冲器容量,对视频质量和主动跳帧进行控制,使缓存满度的减小不会导致控制器无法精准调节后续帧量化参数。由实验结果可知,该方法最小控制误差为0.07,能够有效提高视频质量。     

一种从MPEG视频流中快速分割镜头的算法

镜头分割算法是实现视频检索的关键,本文提出一种针对MPEG视频流的快速分割镜头的算法,介绍了该算法的基本原理与实现过程。该算法利用压缩视频中的可用信息,通过计算帧的内编码宏块数量的比例作为是否需要进行镜头分割判别的标识,进而计算MPEG视频流B帧各宏块编码类型来检测发生镜头分割的帧住置,并进行了相关的实验。实验
结果表明,该算法能快速有效地检测镜头分割,且计算量较小。     

A fast frame type selection technique for very low bit rate coding using MPEG-1

In this paper we present an adaptive frame type selection algorithm for motion compensation, which is applied to a low bit rate video coding using MPEG-1. In the adaptive scheme, the number of reference frames for motion compensation is determined by a scene change detection algorithm using temporal segmentation. To choose for the distance measure for the temporal segmentation, three histogram-based measures and one variance-based measure were tested and compared. The reference frame positions may be determined by an exhaustive search algorithm which is computationally complex. The complexity can be reduced by using a binary search algorithm which exploits the monotonicity of the distance measure with respect to the reference frame interval. The target bit allocation for each picture type in a group of pictures is adjusted to allow a variable number of reference frames with the constraint of constant channel bit rate. Simulation results show that the adaptive reference frame positioning scheme compares favorably with the fixed positioning scheme at the bit rates of 64 kb/s and 14.4 kb/s.     

Online smoothness with dropping partial data based on advanced video coding stream

Most studies of smoothing video stream compute the required bit rate of video transmission to satisfy all the transmitted data. In this paper, our proposed online smoothing with tolerable data dropping algorithm can adjust the bit rate as smooth as possible. Several multimedia encoding schemes, such as advanced video coding (AVC), can support partial data dropping to adapt to available bandwidth network. The AVC stream can be adapted by smoothing algorithm to ensure video quality for a given set of constraints where these constraints may be either static after the session set up or may dynamically change over the session duration. Our algorithm is based on the online minimum variance bandwidth allocation algorithm to look ahead a window of frames, dynamically adjusting the required bit rate such that ensuring smoothness when the buffer encounters underflow or overflow for video stream. Furthermore, we add the scheme of data dropping into this algorithm to increase the possibility of smoothing bit rates. The experimental results show the peak rate, the average ratio of dropped data, and the coefficient of variation for five test sequences with different content characteristics such as the average frame size, the peak/mean ratio of frame size, and the average frame bit rate. Experimental parameters are varied by window sizes and tolerable dropping ratios. The algorithm can significantly reduce the peak rate and the coefficient of variation when the transmitted packets are allowed dropping by a user-defined dropping ratio.     

基于H.264/AVC的自适应帧级位分配优化算法*

为了获得精确的帧级目标位分配和提高编码质量,在JVT-G012码率控制算法的基础上,提出一种自适应的帧级位分配优化算法。该算法充分考虑帧之间纹理复杂度,弥补了JVT-G012算法中对帧目标位平均分配算法的不足。大量实验结果表明,改进后的算法在高运动或场景切换情况下,能明显提高视频编码质量,实现目标位的优化分配和输出码率的精确控制。     

以运动矢量残差为载体的视频隐写算法

目的 以运动矢量（MV）为载体的视频隐写算法会破坏同一帧内相邻宏块或者相邻帧相同位置宏块的运动矢量之间的相关性,从而容易被基于运动矢量时空相关性（temporal-spatial correlation）特征的隐写分析算法检测到。为了解决这个问题,在H.264/AVC的视频编解码标准下构建了一种能抵抗基于运动矢量时空相关性隐写分析的视频隐算法。方法 通过分析运动矢量残差（MVD）与运动矢量时空相关性的联系,证明了保持运动矢量残差的统计特征的隐写算法能够很好地保持视频运动矢量的时空相关性;通过分析运动矢量残差的统计特征设置了一种能保持其直方图特征的嵌入规则,使用4个标记符和一个队列来记录修改载体造成的特征改变,并进行相应的补偿操作,将秘密信息嵌入到视频压缩过程中的熵编码之前的运动矢量残差中;结合可变长度的矩阵编码,有效降低了嵌入秘密信息对载体的修改量。结果 实验结果表明,该算法能较好地保持运动矢量残差在隐写前后的直方图特征,具有较好的视觉不可见性,对视频峰值信噪比（PSNR）和码率影响都不超过0.5%,满载嵌入的情况下基于运动矢量时空相关性的隐写分析算法对其的检测正确率只有70%左右。结论 本文算法以运动矢量残差为隐写嵌入的载体,使用保持其直方图特征的嵌入规则,结合了矩阵编码以减低对载体的修改量,能较好抵抗基于运动矢量时空相关性的隐写分析。     

Dynamic Bit Allocation for Multiple Video Object Coding

In MPEG-4, a visual scene may be treated as a composition of video objects and coded at object level. Such a flexible video coding framework makes it possible to code different video objects with different priority according to human perceptual characteristics. In this paper, we introduce a novel dynamic bit allocation framework to improve the subjective quality in such an object-based video coding system. We incorporate the rate distortion models with the dynamic priorities of the video objects and jointly encode video objects to minimize the weighted distortion within the bit budget constraint. We guarantee the human-interested video objects a better reconstructed quality by using the weighted bit allocation strategy in favour of the video objects with higher priority. To obtain the priority automatically, we apply a visual attention model. Comparing with traditional bit allocation algorithms, the objective quality of the object with higher priority is significantly improved under this framework. These results demonstrate the usefulness of this dynamic bit allocation framework     

仿射不变轮廓匹配的视频拼接研究

为了解决复杂场景变换时视频拼接的精度问题,提出了一种仿射不变轮廓匹配的拼接算法——利用场景中主要区域的轮廓信息对视频图像进行匹配,然后利用匹配点求解运动参数进行拼接。该方法克服了传统拼接算法在复杂的场景变化以及重叠区小的情况下拼接精度低的问题。与基于SIFT的拼接算法对比表明,该算法实现了图像序列的高精度拼接,不仅能适应仿射变换,并且对于重叠区域小,存在运动遮挡的视频具有一定的鲁棒性。     

A new multi-level statistical model for variable bit rate MPEG sources over ATM networks and its performance study

In this paper, we propose a new traffic model for MPEG-coded video sequences. The proposed modeling scheme uses scene-based traffic characteristics and considers the correlations between frames of consecutive group of pictures (GOPs). Using a simple scene detection algorithm, scene changes are modeled by a state transition matrix and the number of GOPs of a scene state is modeled by a geometric distribution. Frames of a scene are modeled by the mean I, P, and B frame sizes of each state. For more accurate traffic modeling, the residual bits that represent the difference between the original frame size and the mean frame size of each frame type are compensated by autoregressive processes. The modeling results show that our scene-based model can capture the statistical traffic characteristics of the original video sequences well and estimate the queueing performance with good approximation quality.     

基于骨架特征的人数统计

针对视频监控中行人在运动中将出现部分或严重遮挡的问题,提出了一种基于人体骨架特征的人数统计算法。首先,利用形态学骨架提取算法提取初始人体骨架图;然后,剔除骨架孤立点和骨架伪分支,得到最优人体骨架特征;最后,通过分析骨架的人头区域特征,建立人头检测响应规则,检测行人人头个数实现人数统计。实验结果表明,该算法能够解决视频监控人物相互之间部分遮挡和严重遮挡问题,针对相对稀疏的场景该算法人数统计准确率为95%左右。     

Automatic scene detection for advanced story retrieval

Browsing video scenes is just the process to unfold the story scenarios of a long video archive, which can help users to locate their desired video segments quickly and efficiently. Automatic scene detection of a long video stream file is hence the first and crucial step toward a concise and comprehensive content-based representation for indexing, browsing and retrieval purposes. In this paper, we present a novel scene detection scheme for various video types. We first detect video shot using a coarse-to-fine algorithm. The key frames without useful information are detected and removed using template matching. Spatio-temporal coherent shots are then grouped into the same scene based on the temporal constraint of video content and visual similarity of shot activity. The proposed algorithm has been performed on various types of videos containing movie and TV program. Promising experimental results shows that the proposed method makes sense to efficient retrieval of video contents of interest.     

MPEG VBR视频流—统计特性及其模型

该文分析了已有的MPEG VBR视频流模型及其缺点,并在此基础上对VBR视频流的统计特性进行了研究,实验结果表明,通过对整个视频流进行场景划分（聚类）,聚类间用Markov调制链建模,而每一聚类中独立的场景则可以采用TES模型基于GOP（Group Of Picture)而非帧进行建模,则该方法既能避免状态空间过大,又能避免帧间周期性的自相关,因而能够更好地拟合VBR视频流序列的一阶和二阶统计特性,同时,对独立场景的GOP分布函数可以采用Gamma函数进行拟合,自相关函数则可以采用双指数函数更好地拟合。     

基于非局部低秩和自适应量化约束先验的HEVC后处理算法

经高效视频编解码标准HEVC压缩后的视频在高压缩比、低码率的情况下存在明显的压缩效应。针对该问题,提出了一种基于非局部低秩(Non-local Low-rank, NLLR)和自适应量化约束(Adaptive Quantization Constraint, AQC)先验的HEVC后处理算法。该算法首先构造在最大后验概率框架下的优化问题,然后利用解码后的压缩视频和量化参数QP获取非局部低秩和自适应量化约束先验信息,最后利用split-Bregman迭代算法来解决所提的优化问题,从而有效去除压缩效应,提升重建视频质量。其中,非局部低秩先验通过构建基于相似块聚类的非局部低秩模型来获得;自适应量化约束先验通过联合不同量化参数QP下的约束特性与视频的DCT域块活动性来获得。实验结果表明,在同等码率的情况下,与HEVC标准相比,所提算法在帧内编码模式下可以达到平均0.259 7 dB的PSNR提升,在帧间编码模式下可以达到平均0.282 8 dB的PSNR提升。     

基于压缩域信息的立体视频对象分割方法

立体视频对象分割是交互式多视点视频应用的关键技术。为了提高对象分割的时效性和精确性,提出了一种利用压缩域视差和运动信息的立体视频对象分割算法。该算法首先对运动矢量场和视差场进行提取和修正处理,然后对视频帧进行分割作为初始值,最后用均值偏移算法聚类得到最终的对象分割结果。实验结果表明,对于纹理复杂的场景有很好的分割效果,可以获得与语义一致的对象。     

A study on visual sensor network cross-layer resource allocation using quality-based criteria and metaheuristic optimization algorithms

Visual sensor networks (VSNs) consist of spatially distributed video cameras that are capable of compressing and transmitting the video sequences they acquire. We consider a direct-sequence code division multiple access (DS-CDMA) VSN, where each node has its individual requirements in compression bit rate and energy consumption, depending on the corresponding application and the characteristics of the monitored scene. We study two optimization criteria for the optimal allocation of the source and channel coding rates, which assume discrete values, as well as for the power levels of all nodes, which are continuous, under transmission bit rate constraints. The first criterion minimizes the average distortion of the video received by all nodes, while the second one minimizes the maximum video distortion among all nodes. The resulting mixed integer optimization problems are tackled with a modern optimization algorithm, namely particle swarm optimization (PSO), as well as a hybrid scheme that combines PSO with the deterministic Active-Set optimization method. Extensive experimentation on interference-limited as well as noisy environments offers significant intuition regarding the effectiveness of the considered optimization schemes, indicating the impact of the video sequence characteristics on the joint determination of the transmission parameters of the VSN.