A HEVC Video Steganalysis Method Using the Optimality of Motion Vector Prediction

Among steganalysis techniques,detection against MV(motion vector)domain-based video steganography in the HEVC(High Efficiency Video Coding)standard remains a challenging issue.For the purpose of improving the detection performance,this paper proposes a steganalysis method that can perfectly detectMV-based steganography in HEVC.Firstly,we define the local optimality of MVP(Motion Vector Prediction)based on the technology of AMVP(Advanced Motion Vector Prediction).Secondly,we analyze that in HEVC video,message embedding either usingMVP index orMVD(Motion Vector Difference)may destroy the above optimality of MVP.And then,we define the optimal rate of MVP as a steganalysis feature.Finally,we conduct steganalysis detection experiments on two general datasets for three popular steganographymethods and compare the performance with four state-ofthe-art steganalysis methods.The experimental results demonstrate the effectiveness of the proposed feature set.Furthermore,our method stands out for its practical applicability,requiring no model training and exhibiting low computational complexity,making it a viable solution for real-world scenarios.

Secure Transmission of Compressed Medical Image Sequences on Communication Networks Using Motion Vector Watermarking

Medical imaging plays a key role within modern hospital management systems for diagnostic purposes.Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed,all while upholding image quality.Moreover,an increasing number of hospitals are embracing cloud computing for patient data storage,necessitating meticulous scrutiny of server security and privacy protocols.Nevertheless,considering the widespread availability of multimedia tools,the preservation of digital data integrity surpasses the significance of compression alone.In response to this concern,we propose a secure storage and transmission solution for compressed medical image sequences,such as ultrasound images,utilizing a motion vector watermarking scheme.The watermark is generated employing an error-correcting code known as Bose-Chaudhuri-Hocquenghem(BCH)and is subsequently embedded into the compressed sequence via block-based motion vectors.In the process of watermark embedding,motion vectors are selected based on their magnitude and phase angle.When embedding watermarks,no specific spatial area,such as a region of interest(ROI),is used in the images.The embedding of watermark bits is dependent on motion vectors.Although reversible watermarking allows the restoration of the original image sequences,we use the irreversible watermarking method.The reason for this is that the use of reversible watermarks may impede the claims of ownership and legal rights.The restoration of original data or images may call into question ownership or other legal claims.The peak signal-to-noise ratio(PSNR)and structural similarity index(SSIM)serve as metrics for evaluating the watermarked image quality.Across all images,the PSNR value exceeds 46 dB,and the SSIM value exceeds 0.92.Experimental results substantiate the efficacy of the proposed technique in preserving data integrity.

Dynamic Hand Gesture-Based Person Identification Using Leap Motion and Machine Learning Approaches

Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.

虚拟场景中基于Motion Vector的人群图像绘制算法

针对虚拟场景中大规模人群图像绘制时由于采集图像数量有限,在视点连续变化时出现跳变的问题,提出了一种基于Motion Vector的图像绘制算法,该算法通过移动原始图像的像素位置生成相邻视点位置的图像,使得各个离散采样之间能够连续过渡,很好地解决了由于采样不足而引起的跳变问题,同时保证了绘制系统的实时性,实验结果验证了该算法的有效性。

Derivation of Cloud-Free-Region Atmospheric Motion Vectors from FY-2E Thermal Infrared Imagery

The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors （AMVs） in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference （NEdT） performance of FY-2E split win- dow （10.3-11.5 μm, 11.6-12.8 μm） channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference （SD） methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the ＂truth＂. The results show that all three algorithms, though not perfect in some cases, generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 hPa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.

An efficient compressed domain moving object segmentation algorithm based on motion vector field

In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector （MV） field parsed from the compressed video is the only cue used for moving object segmentation. First the MV field is temporally and spatially normalized, and then accumulated by an iterative backward projection to enhance salient motions and alleviate noisy MVs. The accumulated MV field is then segmented into motion-homogenous regions using a modified statistical region growing approach. Finally, moving object regions are extracted in turn based on minimization of the joint prediction error using the estimated motion models of two region sets containing the candidate object region and other remaining regions, respectively. Experimental results on several H.264 compressed video sequences demonstrate good segmentation performance.

Propagating adaptive-weighted vector median filter for motion-field smoothing

In the field of predictive video coding and format conversion, there is an increasing attention towards estimation of the true inter-frame motion. The restoration of motion vector field computed by 3-D RS is addressed and a propagating adaptive-weighted vector median (PAWVM) post-filter is proposed. This approach decomposes blocks to make a better estimation on object borders and propagates good vectors in the scanning direction. Furthermore, a hard-thresholding method is introduced into calculating vector weights to improve the propagating. By exploiting both the spatial correlation of the vector field and the matching error of candidate vectors, PAWVM makes a good balance between the smoothness of vector field and the prediction error, and the output vector field is more valid to reflect the true motion.

Characteristics of Fengyun-4A Satellite Atmospheric Motion Vectors and Their Impacts on Data Assimilation

The high observation efficiency,scanning speed and observation frequency of the Fengyun-4A(FY-4A)satellite indicates the progress of Chinese geostationary meteorological satellites.The characteristics of FY-4A atmospheric motion vectors(AMVs)derived from the high-level water vapor(WV-High)channel,mid-level water vapor(WV-Mid)channel,and infrared(IR)channel of FY-4A are analyzed,and their corresponding observation errors estimated.Then,the impacts of single-channel and multi-channel FY-4A AMVs on RMAPS-ST(the Rapid-refresh Multi-scale Analysis and Prediction System-Short Term)are evaluated based on one-month data assimilation cycling and forecasting experiments.Results show that the observation errors of FY-4A AMVs from the three channels have an explicit vertical structure.Results from the cycling experiments indicate that the assimilation of AMVs from WV-High produces more apparent improvement of the wind in the upper layer,while a more positive effect in the lower layer is achieved by the assimilation of AMVs from IR.Furthermore,the assimilation of AMVs from IR is more skillful for medium and moderate precipitation than from other channels owing to the good quality of data in the lower layer in the AMVs from IR.Assimilation of FY-4A AMVs from the three channels could combine the advantages of assimilation from each individual channel to improve the wind in the upper,middle and lower layers simultaneously.

Cooperative Navigation for Autonomous Underwater Vehicles Based on Estimation of Motion Radius Vectors

A cooperative navigation algorithm for a group of autonomous underwater vehicles is proposed on the basis of motion radius vector estimation.Combined the dead reckoning data with the mutual range data through an acoustic communication network among the group members, the relative positioning problem can be solved. A novel approach for solving the relative positioning is presented by using a recursive trigonometry technique and extended Kalman filter(EKF). Simulation results verify the correctness and effectiveness of this navigation method.

MOTION VECTOR RECOVERY METHOD BASED ON MEAN SHIFT PROCEDURE

This letter presents a novel Motion Vector (MV) recovery method which is based on Mean Shift (MS) procedure. According to motion continuity, MVs in local area should be similar. If projecting MV into 2-D feature space, local MVs in the feature space tend to cluster closely. To estimate the lost MVs in local area, recovery of lost MVs is modeled as clustering operation. MS procedure is applied to enforce each lost MV in the feature space to shift to the position where dominant MVs are gathered. Meanwhile, bandwidth estimation is statistically characterized by the variation of local standard de-viations; weighted value calculation is determined by estimation of overall standard deviation. Simu-lation results demonstrate their better performance when compared with other MV recovery ap-proaches and low computation cost.

Comparative Analysis of the Generalized Omega Equation and Generalized Vertical Motion Equation

Research on vertical motion in mesoscale systems is an extraordinarily challenging effort.Allowing for fewer assumptions,a new form of generalized vertical motion equation and a generalized Omega equation are derived in the Cartesian coordinate system(nonhydrostatic equilibrium)and the isobaric coordinate system(hydrostatic equilibrium),respectively.The terms on the right-hand side of the equations,which comprise the Q vector,are composed of three factors:dynamic,thermodynamic,and mass.A heavy rain event that occurred from 18 to 19 July 2021 in southern Xinjiang was selected to analyze the characteristics of the diagnostic variable in the generalized vertical motion equation(Qz)and the diagnostic variable in the generalized Omega equation(Qp)using high-resolution model data.The results show that the horizontal distribution of the Qz-vector divergence at 5.5 km is roughly similar to the distribution of the Qp-vector divergence at 500 hPa,and that both relate well to the composite radar reflectivity,vertical motion,and hourly accumulated precipitation.The Qz-vector divergence is more effective in indicating weak precipitation.In vertical cross sections,regions with alternating positive and negative large values that match the precipitation are mainly concentrated in the middle levels for both forms of Q vectors.The temporal evolutions of vertically integrated Qz-vector divergence and Qp-vector divergence are generally similar.Both perform better than the classical quasigeostrophic Q vector and nongeostrophic Q vector in indicating the development of the precipitation system.

Dynamics of Quantum State and Effective Hamiltonian with Vector Differential Form of Motion Method

Effective Hamiltonians in periodically driven systems have received widespread attention for realization of novel quantum phases, non-equilibrium phase transition, and Majorana mode. Recently, the study of effective Hamiltonian using various methods has gained great interest. We consider a vector differential equation of motion to derive the effective Hamiltonian for any periodically driven two-level system, and the dynamics of the spin vector are an evolution under the Bloch sphere. Here, we investigate the properties of this equation and show that a sudden change of the effective Hamiltonian is expected. Furthermore, we present several exact relations, whose expressions are independent of the different starting points. Moreover, we deduce the effective Hamiltonian from the high-frequency limit, which approximately equals the results in previous studies. Our results show that the vector differential equation of motion is not affected by a convergence problem, and thus, can be used to numerically investigate the effective models in any periodic modulating system. Finally, we anticipate that the proposed method can be applied to experimental platforms that require time-periodic modulation, such as ultracold atoms and optical lattices.

Real-time traffic information extraction based on compressed video with interframe motion vector

Extraction of traffic information from image or video sequence is a hot research topic in intelligenttransportation system and computer vision. A real-time traffic information extraction method based on com-pressed video with interframe motion vectors for speed, density and flow detection, has been proposed for ex-traction of traffic information under fixed camera setting and well-defined environment. The motion vectors arefirst separated from the compressed video streams, and then filtered to eliminate incorrect and noisy vectors u-sing the well-defined environmental knowledge. By applying the projective transform and using the filtered mo-tion vectors, speed can be calculated from motion vector statistics, density can be estimated using the motionvector occupancy, and flow can be detected using the combination of speed and density. The embodiment of aprototype system for sky camera traffic monitoring using the MPEG video has been implemented, and experi-mental results proved the effectiveness of the method proposed.

Frame interpolation with pixel-level motion vector field and mesh based hole filling

Most of the traditional methods are based on block motion compensation tending to involve heavy blocking artifacts in the interpolated frames. In this paper, a new frame interpolation method with pixel-level motion vector field （MVF） is proposed. Our method consists of the following four steps： （i） applying the pixel-level motion vectors （MVs） estimated by optical flow algorithm to eliminate blocking artifacts （ii） motion post-processing and super-sampling anti-aliasing to solve the problems caused by pixel-level MVs （iii） robust warping method to address collisions and holes caused by occlusions （iv） a new holes filling method using triangular mesh （HFTM） to reduce the artifacts caused by holes. Experimental results show that the proposed method can effectively alleviate the holes and blocking artifacts in interpolated frames, and outperforms existing methods both in terms of objective and subjective performances, especially for sequences with complex motions.

基于双域标记的视频鲁棒可逆水印算法

针对现有视频水印算法无法兼顾鲁棒性与可逆性的问题,文章提出一种基于双域标记的视频鲁棒可逆水印算法。该算法在H.264视频编码中的量化DCT系数域利用传统鲁棒水印拼接技术,嵌入水印信息;在运动矢量域利用二维直方图迁移技术,嵌入辅助信息,实现解码端的水印提取与原始视频的无损恢复。实验结果表明,文章算法具有良好的不可见性,实验视频的峰值信噪比与结构相似度均值分别为44.7537 dB与0.9902,比特率扩张均在16.74%以下,同时对不同强度的失真攻击均具有强鲁棒性,实验视频的归一化互相关系数均在0.970以上,误码率均在0.068以下。

基于激光SLAM辅助的陆用惯导行进间粗对准方法

目前常见的陆用惯导系统的行进间对准方法往往存在一些各自的问题,如GPS辅助时容易受到信号遮蔽影响;而里程计辅助时往往会受到机动路线约束的限制。针对这些问题,提出了一种激光SLAM系统信息辅助的陆用惯性导航系统(SINS)行进间粗对准算法,推导了基于激光SLAM系统视在速度观测矢量的姿态矩阵更新算法,利用基于REQUEST的双矢量定姿方法,实现初始常值姿态矩阵C_(b)^(n)(0)的求取,完成行进间的姿态粗对准和定位导航。在实验室无人车实验中,所提方法的对准姿态误差比里程计辅助的方法减小了约56%;同时与合作单位的综合实验验证结果表明,在进行250 s的行进间粗对准时,最终时刻的航向角误差为-0.0088°,实现5 min内达到1 mil的粗对准精度,所提算法可以有效实现激光SLAM信息辅助下的陆用惯导的行进间粗对准,并具有较快的收敛速度。

一种基于静止卫星的海面风矢量估测方法

参考大气动力学理论中风随高度、纬度的分布特征,提出一种基于静止卫星低层大气导风利用全连接神经网络估测海面风的新思路,构建基于卫星遥感数据的全连接神经网络海面风矢量估测模型,实现基于大气导风的海面风估测。基于GOES-16先进基线成像仪可见光通道0.5 km分辨率大气导风开展试验,并与2021年1月1日—12月31日北美近海岸和海上93个美国国家数据浮标中心浮标数据比对,结果表明:全连接神经网络估算得到基于大气导风的海面风风速均方根误差不大于1.5 m·s^(-1),较传统模型降低0.24 m·s^(-1)。将模型应用于飓风场景,通过与2022年3个北大西洋飓风和3个东太平洋飓风共13个时次的再分析数据比对表明:基于大气导风的海面风风速均方根误差不大于1.1 m·s^(-1),相较于传统经验模型降低0.04 m·s^(-1),在低风速区无系统性偏差。

AN IMPROVED ROTATION VECTOR ATTITUDE ALGORITHM FOR LASER STRAP-DOWN INERTIAL NAVIGATION SYSTEM

The laser gyro is most su it able for building the strap down inertial navigation system (SINS), and its acc uracy of attitude algorithm can enormously affect that of the laser SINS. This p aper develops three improved algorithmal expressions for strap down attitude ut ilizing the angular increment output by the laser gyro from the last two and cur rent updating periods according to the number of gyro samples, and analyses the algorithm error in the classical coning motion. Compared with the conventional algorithms, simulational results show that this improved algorithm has higher precision. A new way to improve the rotation vector algorithms is provided.

基于运动向量修改的保持块间扰动最小的HEVC信息隐藏算法

高效视频编码(High Efficiency Video Coding, HEVC)标准能够大幅度提升压缩效率,正被广泛应用中。为提高基于运动向量修改的HEVC视频隐写算法的安全性,本文结合了HEVC标准中帧间预测编码的新技术,并利用在运动向量域进行信息嵌入扰动较小的优点,提出了一种基于运动向量修改的保持块间扰动最小的HEVC信息隐藏算法。首先,该算法量化了修改运动向量后对当前高级运动向量预测(Advanced Motion Vector Prediction, AMVP)单元和其相邻融合(Merge)模式预测单元产生的扰动代价,将运动向量垂直分量和水平分量之和作为原始载体元素。其次,结合校验网格码(Syndrome Trellis Codes, STC),寻找扰动代价最小的嵌入路径,通过修改运动向量中绝对值较大的分量将信息嵌入在AMVP模式的预测单元运动向量上。此外,为减小对视频质量的影响,利用修改后的运动向量更新运动向量差值。实验结果表明,所提方法对视频序列进行信息嵌入后,由于本文引入的扰动代价判断可以有效控制视频质量变化,对视频序列的峰值信噪比、码率影响较小,所以该方法对视频的扰动很小。而且本文算法不仅在视频质量保护上有良好的性能,还对运动向量域专用隐写分析具有良好的抗检测能力,有利于基于HEVC视频码流的隐蔽通信的进一步发展。

多通道运动矢量排序的可逆视频信息隐藏

针对现有基于运动矢量排序的视频可逆信息隐藏算法无法根据视频帧视觉特性自适应调节嵌入容量且容量有限的问题,提出一种多通道矢量排序的可逆视频信息隐藏算法.该算法通过计算参考帧的纹理复杂度和运动复杂度情况决定后续帧是否嵌入信息,从而实现后续帧的自适应信息嵌入,算法同时对多通道像素值排序(multi-pass pixel value ordering, multi-pass PVO)技术进行改进,将其应用于视频信息隐藏,有效提升可逆隐藏算法嵌入容量.实验结果表明,相较于同类算法,PSNR和SSIM的变化值分别降低14.5%和8.5%,嵌入容量提升7.4%,在视觉质量和嵌入容量方面有显著提高.