Anti-JPEG Compression Steganography Based on the High Tense Region Locating Method

Robust data hiding techniques attempt to construct covert communication in a lossy public channel. Nowadays, the existing robust JPEG steganographic algorithms cannot overcome the side-information missing situation. Thus, this paper proposes a new robust JPEG steganographic algorithm based on the high tense region location method which needs no side-information of lossy channel. First, a tense region locating method is proposed based on the Harris-Laplacian feature point. Then, robust cover object generating processes are described. Last, the advanced embedding cost function is proposed. A series of experiments are conducted on various JPEG image sets and the results show that the proposed steganographic algorithm can resist JPEG compression efficiently with acceptable performance against steganalysis statistical detection libraries GFR (Gabor Filters Rich model) and DCTR (Discrete Cosine Transform Residual).     

Three-dimensional image compression with integer wavelet transforms

A three-dimensional (3-D) image-compression algorithm based on integer wavelet transforms and zerotree coding is presented. The embedded coding of zerotrees of wavelet coefficients (EZW) algorithm is extended to three dimensions, and context-based adaptive arithmetic coding is used to improve its performance. The resultant algorithm, 3-D CB-EZW, efficiently encodes 3-D image data by the exploitation of the dependencies in all dimensions, while enabling lossy and lossless decompression from the same bit stream. Compared with the best available two-dimensional lossless compression techniques, the 3-D CB-EZW algorithm produced averages of 22%, 25%, and 20% decreases in compressed file sizes for computed tomography, magnetic resonance, and Airborne Visible Infrared Imaging Spectrometer images, respectively. The progressive performance of the algorithm is also compared with other lossy progressive-coding algorithms.     

面向航天器结构健康状态监测的数据压缩感知算法研究

航天器产品结构健康状态监测是保证其发射与在轨运行过程中安全平稳运行的重要环节,由于多个传感器在长时间监测过程中会产生大量数据并需要对其进行高效传输和存储,本文针对数据传输问题提出并证明了基于稀疏恢复技术的一种分式最小化模型算法和改进的分式筛选算法,并结合卫星振动试验数据与经典匹配追踪等算法进行了对比分析验证,对比结果表明,在航天器所处环境条件下,所提算法处理得到的数据恢复相对误差均低于两种现有算法,可以在较高压缩比的条件下保证数据恢复的精度,实现了低维数据到高维数据传输。     

基于IHS变换的多光谱遥感图像有损压缩算法

提出了一种有效的多光谱遥感图像有损压缩算法,该算法根据多光谱遥感图像的数据特点,将IHS变换和整数小波变换相结合进行数据压缩.采用IHS变换去除谱间相关性;采用整数小波变换去除空间相关性,依据各个子带的重要程度,用自适应阈值进行量化,并分别对量化后的数据和重要图表采用固定比特平面编码和游程编码.实验结果表明,算法在保证平均PSNR≥33dB时,获得了较高的压缩比,并且算法硬件实现简单,对内存的需求低.     

Radial basis function neural network for pulse radar detection

A new approach using a radial basis function network (RBFN) for pulse compression is proposed. In the study, networks using 13-element Barker code, 35-element Barker code and 21-bit optimal sequences have been implemented. In training these networks, the RBFN-based learning algorithm was used. Simulation results show that RBFN approach has significant improvement in error convergence speed (very low training error), superior signal-to-sidelobe ratios, good noise rejection performance, improved misalignment performance, good range resolution ability and improved Doppler shift performance compared to other neural network approaches such as back-propagation, extended Kalman filter and autocorrelation function based learning algorithms. The proposed neural network approach provides a robust mean for pulse radar tracking     

Prompt photon identification in the ALICE experiment: The isolation cut method

The ALICE experiment at LHC will detect and identify prompt photons and light neutral mesons with the PHOS and EMCal detectors. Charged particles will be detected and identified by the central tracking system. In this paper, a method to identify prompt photons and to separate them from the background of hadrons and decay photons in PHOS with the help of isolation cuts is presented.     

A Distributed Covert Channel of the Packet Ordering Enhancement Model Based on Data Compression

Covert channel of the packet ordering is a hot research topic. Encryption technology is not enough to protect the security of both sides of communication. Covert channel needs to hide the transmission data and protect content of communication. The traditional methods are usually to use proxy technology such as tor anonymous tracking technology to achieve hiding from the communicator. However, because the establishment of proxy communication needs to consume traffic, the communication capacity will be reduced, and in recent years, the tor technology often has vulnerabilities that led to the leakage of secret information. In this paper, the covert channel model of the packet ordering is applied into the distributed system, and a distributed covert channel of the packet ordering enhancement model based on data compression (DCCPOEDC) is proposed. The data compression algorithms are used to reduce the amount of data and transmission time. The distributed system and data compression algorithms can weaken the hidden statistical probability of information. Furthermore, they can enhance the unknowability of the data and weaken the time distribution characteristics of the data packets. This paper selected a compression algorithm suitable for DCCPOEDC and analyzed DCCPOEDC from anonymity, transmission efficiency, and transmission performance. According to the analysis results, it can be seen that DCCPOEDC optimizes the covert channel of the packet ordering, which saves the transmission time and improves the concealment compared with the original covert channel.     

基于工业焊接小车的视觉伺服控制算法研究

针对基于视觉传感器的焊接小车，提出了提高跟踪精度和鲁棒性的视觉伺服控制方法。首先，建立了图像特征的数学模型，并设计了错误数据的检测算法，其次，对于折线焊缝跟踪过程中存在的位置延迟问题，采用了一种自适应视觉伺服控制结构。这种自适应结构在线检测焊缝方向，并能够在焊缝方向发生变化时对控制参数进行相应的调整。针对该控制结构，设计了基于Kalman滤波器的焊缝方向变化检测算法、参考像素坐标调整算法以及预测与实时调整相结合的控制方法。焊缝自动跟踪实验表明所提方法具有较强的鲁棒性和较高的精度。     

Phase unwrapping algorithms for use in a true real-time optical body sensor system for use during radiotherapy

An evaluation of the suitability of eight existing phase unwrapping algorithms to be used in a real-time optical body surface sensor based on Fourier fringe profilometry is presented. The algorithms are assessed on both the robustness of the results they give and their speed of execution. The algorithms are evaluated using four sets of real human body surface data, each containing five-hundred frames, obtained from patients undergoing radiotherapy, where fringe discontinuity is significant. We also present modifications to an existing algorithm, noncontinuous quality-guided path algorithm (NCQUAL), in order to decrease its execution time by a factor of 4 to make it suitable for use in a real-time system. The results obtained from the modified algorithm are compared with those of the existing algorithms. Three suitable algorithms were identified: two-stage noncontinuous quality-guided path algorithm (TSNCQUAL)-the modified algorithm presented here-for online processing and Flynn's minimum discontinuity algorithm (FLYNN) and preconditioned conjugate gradient method (PCG) algorithms for enhanced accuracy in off-line processing.     

Distributed source coding using symbol-based and non-binary turbo codes - applications to wireless sensor networks

A simple but powerful scheme for distributed source coding (DSC) based on the concept of binning and syndromes and non traditional turbo codes is proposed. The previous works on the compression with side information using turbo codes and the binning technique are focused on binary turbo codes. The source is considered to be binary or is converted to a binary stream. This conversion, however, reduces the redundancy that could be exploited by the compression algorithm. To achieve higher compression efficiency, the authors propose using a scheme based on a turbo decoder that decides over symbols rather than bits. In the same direction and for further performance improvement, at the cost of increased encoder complexity, they also present a DSC scheme based on non-binary turbo codes. The results demonstrate improved performance. Based on the suggested algorithms, a scheme for gathering real data in wireless sensor networks and assess the corresponding energy savings is proposed.     

遥感图像客观质量评价方法研究

为分析图像压缩过程对遥感图像质量的影响,从遥感图像构像质量和几何质量两个方面探讨了遥感图像客观质量评价方法,并改进一种基于Harris角点检测算法的亚像素级角点检测算法。采用JPEG2000、SPIHT两种算法分别对这些评价方法进行验证。实验表明：为满足人眼视觉观察能分辨图像细节的要求,遥感图像压缩比不宜超过16倍,为使压缩后图像满足计算机视觉应用,图像压缩比不宜超过8倍。     

数字随动系统的设计和仿真

为满足跟踪系统高速度、高加速度及高精度的要求，在模拟控制系统的基础上，用数字算法代替模拟系统中的位置回路校正电路、速度回路校正电路、脉冲调宽电路，构成数字随动系统，这样它可以有效地采用多种控制算法，实现系统的性能指标，并且系统调试方便，对外的接口少，可靠性高。     

基于YOLOv3和ASMS的目标跟踪算法

为了解决传统算法在全自动跟踪过程中遇到遮挡或运动速度过快时的目标丢失问题,本文提出一种基于YOLOv3和ASMS的目标跟踪算法。首先通过YOLOv3算法进行目标检测并确定跟踪的初始目标区域,然后基于ASMS算法进行跟踪,实时检测并判断目标跟踪效果,通过二次拟合定位和YOLOv3算法实现跟踪目标丢失后的重新定位。为了进一步提升算法运行效率,本文应用增量剪枝方法,对算法模型进行了压缩。通过与当前主流算法进行对比,实验结果表明,本算法能够很好地解决受到遮挡时跟踪目标的丢失问题,提高了目标检测和跟踪的精度,且具有计算复杂度低、耗时少,实时性高的优点。     

基于啁啾脉冲的反射层析激光雷达成像

反射层析激光雷达成像具有系统简单及对湍流不敏感的优势,但普通脉冲发射信号难以兼顾远距离和高精度探测的要求.基于上述情况,本文提出了一种基于啁啾脉冲信号的反射层析激光雷达成像处理方法.该方法首先对啁啾脉冲回波进行相干压缩处理,通过对处理后信号的包络提取得到目标在各方向的反射层析投影数据,最后利用卷积反投影算法实现高分辨力的图像重构.仿真结果表明,在同一投影角度,利用该方法得到的包络与目标反射率投影相一致;在投影角度范围大于60°时能够得到目标的轮廓信息,角度范围越大,成像越精确.研究结果验证了该方法的有效性.     

Lossless and lossy image compression using boolean function minimization

A novel approach for lossless as well as lossy compression of monochrome images using Boolean minimization is proposed. The image is split into bit planes. Each bit plane is divided into windows or blocks of variable size. Each block is transformed into a Boolean switching function in cubical form, treating the pixel values as output of the function. Compression is performed by minimizing these switching functions using ESPRESSO, a cube based two level function minimizer. The minimized cubes are encoded using a code set which satisfies the prefix property. Our technique of lossless compression involves linear prediction as a preprocessing step and has compression ratio comparable to that of JPEG lossless compression technique. Our lossy compression technique involves reducing the number of bit planes as a preprocessing step which incurs minimal loss in the information of the image. The bit planes that remain after preprocessing are compressed using our lossless compression technique based on Boolean minimization. Qualitatively one cannot visually distinguish between the original image and the lossy image and the value of mean square error is kept low. For mean square error value close to that of JPEG lossy compression technique, our method gives better compression ratio. The compression scheme is relatively slower while the decompression time is comparable to that of JPEG.     

Zero-stopping constraint-based hybrid tracking model for dynamic and high-dense crowd videos

Owing to the importance of video surveillance in the public area, tracking finds significant applications using computer vision algorithms to observe the activity of human. In tracking, multi-object tracking is an active research to analyse and detect the activity of anomalies in the crowded scenes. Accordingly, different multi-object tracking algorithms are proposed in the literature to track the human behaviour of the crowded scenes. In this paper, we have presented a zero-stopping criteria-based hybrid tracking algorithm for high-dense crowd videos. Here, head objects are detected using the proposed objective function which considers both colour and texture property of videos. Then, tracking based on motion is performed using the proposed HSIM measure which includes structural similarity (SSIM) and the proposed similarity function. Along with, the data prediction model, exponential weighted moving average (EWMA), is also utilised to track the spatial location of human objects. These two tracking models are then hybridised to obtain the final tracked output. The experimentation is performed with three marathon sequences and the performance is evaluated with particle filtering-based algorithm using tracking number, tracking distance and optimal subpattern assignment metric (OSPA).     

光电成像导引头抗干扰性能评估方法

提出了一种新的光电(红外/电视)成像导引头抗干扰性能评估方法,该半实物仿真系统采用光电跟踪仪模拟导引头的探测器,导引头图像处理单元由DSP系统硬件实现。在线实时评估方式模拟了导引头的实际工作过程,离线事后评估可以改进导引头的图像处理算法。作为一个通用评估平台,此方案可以评价不同导引头的抗干扰性能。