基于快速轮廓转动力矩特征的激光主动成像目标识别

针对激光主动成像的图像特性,提出一种基于快速轮廓转动力矩的目标识别方法。将转动力矩的概念引入目标识别中,提出的快速轮廓转动力矩特征(FCTF)不仅包含了轮廓的尺寸、位置、规则度以及目标的亮暗等信息,同时对于旋转、尺度缩放等变换具有不变性。采用转动力矩的快速计算方法,提高了识别算法的计算效率。识别算法首先使用最大稳定极值区域(MSER)算法检测出目标特征区域,并将其变换为圆形区域,然后结合快速转动力矩特征算法提取出目标区域的局部不变特征,最后输入训练好的支持向量机分类器进行识别。实验结果表明相比于已有的激光主动成像目标识别方法,所提算法对于旋转、仿射变换均具有更高的识别率,同时单帧平均运算时间为9.68 ms,满足激光主动成像目标识别系统实时性的要求。     

Extracting salient region for pornographic image detection

Content-based pornographic image detection, in which region-of-interest (ROI) plays an important role, is effective to filter pornography. Traditionally, skin-color regions are extracted as ROI. However, skin-color regions are always larger than the subareas containing pornographic parts, and the approach is difficult to differentiate between human skins and other objects with the skin-colors. In this paper, a novel approach of extracting salient region is presented for pornographic image detection. At first, a novel saliency map model is constructed. Then it is integrated with a skin-color model and a face detection model to capture ROI in pornographic images. Next, a ROI-based codebook algorithm is proposed to enhance the representative power of visual-words. Taking into account both the speed and the accuracy, we fuse speed up robust features (SURF) with color moments (CM). Experimental results show that the precision of our ROI extraction method averagely achieves 91.33%, more precisely than that of using the skin-color model alone. Besides, the comparison with the state-of-the-art methods of pornographic image detection shows that our approach is able to remarkably improve the performance.     

Image fusion based on shearlet transform and regional features

In this paper, a new image fusion method is proposed based on the shearlet transform. In this method, to make the best use of the regional characteristics of the low frequency coefficients, the low frequency sub-band coefficients from different images are fused according to a rule based on regional energy. As for the high frequency sub-band coefficients, they are fused according to a novel rule upon comprehensive consideration of multiple regional features, such as regional variance, regional average gradient, regional spatial frequency. Experimental results show that the proposed algorithm for image fusion outperforms traditional ones.     

面向海上目标的海陆分离方法研究

随着信息技术的发展,越来越多的国家将关注焦点放在海洋上。快速有效地将海洋与陆地分离对实现海上目标解译、目标检测、识别与提取以及场景理解等具有重要的作用。首先介绍了海陆分离的重要意义和主要内容,在总结各海陆分离方法的基础上将其分为基于先验信息的海陆分离和基于图像特征差异的海陆分离两大类;然后对各方法进行了系统的综述并进行对比分析,指出存在的一些问题;最后给出了总结和展望。     

New approach to the Lax‐Wendroff modified differential equation for linear and nonlinear advection

The paper presents an enhanced analysis of the Lax‐Wendroff difference scheme—up to the eighth‐order with respect to time and space derivatives—of the modified‐partial differential equation (MDE) of the constant‐wind‐speed advection equation. The modified equation has been so far derived mainly as a fourth‐order equation. The Π ‐form of the first differential approximation (differential approximation or equivalent equation) derived by expressing the time derivatives in terms of the space derivatives is used for presenting the MDE. The obtained coefficients at higher order derivatives are analyzed for indications of the character of the dissipative and dispersive errors. The authors included a part of the stencil applied for determining the modified differential equation up to the eighth‐order of the analyzed modified differential equation for the second‐order Lax‐Wendroff scheme. Neither the derived coefficients at the space derivatives of order p ∈ (7 – 8) in the modified differential equation for the Lax‐Wendroff difference scheme nor the results of analyses on the basis of these coefficients of the group velocity, phase shift errors, or dispersive and dissipative features of the scheme have been published. The MDEs for 2 two‐step variants of the Lax‐Wendroff type difference schemes and the MacCormack predictor–corrector scheme (see MacCormack's study) constructed for the scalar hyperbolic conservation laws are also presented in this paper. The analysis of the inviscid Burgers equation solution with the initial condition in a form of a shock wave has been discussed on their basis. The inviscid Burgers equation with the source is also presented. The theory of MDE started to develop after the paper of C. W. Hirt was published in 1968.     

Node Features Adjusted Stochastic Block Model

Stochastic block model (SBM) and its variants are popular models used in community detection for network data. In this article, we propose a feature-adjusted stochastic block model (FASBM) to capture the impact of node features on the network links as well as to detect the residual community structure beyond that explained by the node features. The proposed model can accommodate multiple node features and estimate the form of feature impacts from the data. Moreover, unlike many existing algorithms that are limited to binary-valued interactions, the proposed FASBM model and inference approaches are easily applied to relational data that generate from any exponential family distribution. We illustrate the methods on simulated networks and on two real-world networks: a brain network and an US air-transportation network.     

A Note on Strong Edge Coloring of Sparse Graphs

A strong edge coloring of a graph is a proper edge coloring where the edges at distance at most 2 receive distinct colors. The strong chromatic index χ'_s(G) of a graph G is the minimum number of colors used in a strong edge coloring of G. In an ordering Q of the vertices of G, the back degree of a vertex x of G in Q is the number of vertices adjacent to x, each of which has smaller index than x in Q. Let G be a graph of maximum degree Δ and maximum average degree at most 2 k. Yang and Zhu [J. Graph Theory, 83, 334–339(2016)] presented an algorithm that produces an ordering of the edges of G in which each edge has back degree at most 4 kΔ-2 k in the square of the line graph of G, implying that χ'_s(G) ≤ 4 kΔ-2 k + 1. In this note, we improve the algorithm of Yang and Zhu by introducing a new procedure dealing with local structures. Our algorithm generates an ordering of the edges of G in which each edge has back degree at most(4 k-1)Δ-2 k in the square of the line graph of G, implying that χ'_s(G) ≤(4 k-1)Δ-2 k + 1.     

HXD3型电力机车交流传动系统仿真分析

针对HXD3型电力机车的主传动和辅助传动系统采用了交流传动技术,通过介绍HXD3型电力机车牵引变流器的工作原理,对HXD3型电力机车的主传动系统进行了仿真分析,仿真结果表明基于交－直－交传动方式的牵引变流器应用于机车时具有良好的牵引特性,功率因数高,且谐波干扰小。     

基于支撑集保护的回环匹配算法

针对部分压缩感知贪婪迭代类重构算法中误删正确支撑集元素的缺点,提出了一种基于支撑集保护的回环匹配算法（LM-P）。该算法依据最小残差内积初始化非受保护支撑集元素,然后依据观测向量在非受保护支撑集对应观测子矩阵上的投影,选择对应投影绝对值最大的元素添加到受保护支撑集,迭代获得受保护支撑集,从而重构原始信号。实验结果表明,对于非零值服从正态分布且稀疏度小于观测值一半数目的稀疏信号,LM-P算法的重构准确率超过86%;对于低信噪比稀疏信号,该算法的重构准确率能够维持在99%以上;与OMP、CoSaMP、SP和GPA算法相比,LM-P精确重构所需观测值数更少;此外,LM-P算法在二维图像信号的重构中也有较好性能。     

基于稀疏表示和道路辅助的单幅SAR图像运动目标检测方法

本文提出一种利用单幅SAR(Synthetic Aperture Radar)图像实现运动目标检测的方法.首先提出一种基于压缩感知的SAR图像道路检测算法:根据SAR图像中道路的特点,使用模糊C均值方法将图像进行模糊分类,获得大致的道路区域,然后利用Hough变换域的稀疏性,用压缩感知精确定位图像中的道路信息.其次利用图像稀疏表示的方法对运动目标进行检测:不同速度运动目标的散焦量和距离单元跨越不同,由此生成样本图像,继而构造超完备字典.将待测图像分块,并计算子图像在字典下的稀疏系数,检测并匹配出运动目标的速度参数.最后,结合已检测出的道路辅助信息,消除多普勒模糊影响,剔除虚假的运动目标,并对运动目标速度参数进行校正.实验结果证明了所提方法的有效性.