基于最大类间方差准则的变化区域提取

针对不同时相遥感影像变化检测研究中变化区域的自动提取问题,本文提出一种基于类间最大方差准则,利用C均值算法自动确定变化阈值的方法.该方法中将变化区域提取问题转化为两类之间的分类问题,利用C均值算法进行迭代处理,当两类之间方差最大时即为最佳变化阈值T.实验结果表明,该方法可准确快速地确定图像变化检测的最佳阈值,实现变化区域提取的自动化.     

一种多尺度和聚类分析的变化检测

针对多时相遥感影像变化检测问题,提出了一种多尺度和聚类分析的变化检测方法。该方法在差异影像的基础上,利用均值平移算法对差值法构造的差异影像进行平滑,结合平稳小波变换对平滑后的差异图像做两层的小波分解,由此构造由平滑后的差异图像以及提取的小波系数组成的特征向量,用 K 均值聚类对特征向量分类,通过区域生长将各类合并得到变...     

Shearlet多方向自适应加权融合的稀疏表征人脸识别

针对传统稀疏表征分类器只有在训练样本足够多时才会对特征变化不敏感的缺点,提出一种Shearlet多方向自适应加权融合的稀疏表征人脸识别算法。为了提取局部方向信息并降低特征维数,首先利用Shearlet变换对图像进行多尺度、多方向分解,获得子带系数矩阵,然后根据子带系数矩阵方差的大小对同一尺度的方向子图按主方向排序,利用子带系数矩阵的能量和均值特征对排序后的人脸子图进行加权融合,最后为了使得表征系数矢量具有更为显著的稀疏性,进一步利用融合特征构造字典。在ORL、FERET和YALE人脸库中做了多组实验,结果表明,该方法能增强对外界环境变化的鲁棒性,同时可以提高人脸的识别率。     

基于刚性运动模型的全局运动矢量探测方法

针对帧间旋转图像序列的稳定处理,提出一种新的运动矢量探测方法.首先进行多区域的块匹配,得到不同区域的局部平移运动矢量;然后利用刚性运动模型,获得包含旋转角度的全局运动矢量.与平移运动模型相比,刚性运动模型更加符合帧间运动的真实过程,因而本方法具有更好的稳像效果.航拍图像处理结果表明,帧间峰值信噪比达到29.47 dB,比基于平移运动模型的方法提高2.02 dB.     

基于改进活动轮廓模型的矢量边界更新方法

针对GIS中地物矢量边界更新繁琐和低效的问题,提出了一种基于活动轮廓模型的矢量边界自动更新方法.以现有的GIS矢量边界为初始位置,以遥感影像信息作为轮廓形状演化的驱动力,融合遥感影像与GIS数据信息,在二者交互作用下实现GIS矢量边界更新.针对活动轮廓模型演化过程中缺乏移动范围约束的缺陷,可利用历史遥感影像目标边界点进行采样,估计目标大体轮廓形状,对活动轮廓模型的移动进行约束.实验表明,该方法可得到更好的矢量边界更新效果.     

基于深度置信网络的无人机航拍图像变化检测

无人机(UAV)图像的变化检测对城市规划发展中的城市空间布局、土地利用信息具有重要的意义.针对航拍图像地面背景复杂,传统的变化检测方法鲁棒性低等问题,研究基于深度置信网络(DBN)的无人机航拍图像变化检测方法.利用DBN能够自动学习、提取特征的特点,将DBN应用到无人机图像的变化检测中.首先通过模糊C聚类联合算法对采集的图像进行预分类,并在此基础上进行DBN的逐层预训练;然后利用反向传播算法微调整个网络,从而使网络权值达到最优;最后,将该DBN模型应用于无人机图像的变化检测.实验结果表明,该方法能够有效地提取出图像的变化区域,检测准确率达到95%以上,该方法提高了图像变化检测的精度,实现了图像变化检测的智能化.     

复杂背景下运动目标的提取

提出了在复杂背景以及摄像机运动的情况下运动目标提取的算法。采用了新的局部投影的方法,在图像中合理地划分了投影区域,在求投影偏移量时提出了峰值匹配的算法,合理地检测到了投影偏移量。求得各个局部运动矢量后,采用出现频率最高的局部运动矢量代表全局运动矢量,成功的补偿了背景的运动。实验结果表明该算法在图像背景复杂且由于摄像机运动使背号发生明显变化的情况下,可稳定准确地提取出运动目标,并能有效克服背景中存在的运动干扰。     

动载荷作用下壳体的结构声强分析

结构声强矢量图直观地给出了壳体表面各点能量传输的分布特性。首先推导了壳体局部坐标下的结构声强计算公式,应用坐标转换得到了结构声强的全局坐标表达式,用有限元计算了筒体和板壳组合结构的结构声强,并绘制出了矢量图。结果表明用有限元法对各种壳体的结构声强进行分析是十分有效的。     

遥感图像变化检测算法研究

笔者根据切身工作实践,创新性的提出了一种新型卫星影像的变化检测算法。以非下采样ContourLet变换(NSCT)和脉冲耦合神经网络(PCNN)为基础的算法,实现了传统非下采样变换和脉冲耦合神经网络算法的有机结合,适用于无监督、不同时相的卫星影像的变化检测。     

局部特征点的鲁棒性数字稳像

针对视频序列受载体的影响,本文提出了基于Harris局部特征点的数字稳像方法。局部特征点在图像处理、模式识别、计算机视觉以及目标检测与跟踪领域得到了广泛的研究。首先,利用Harris算法提取动载体摄像系统中每帧图像的局部特征点,采用基于归一化互相关匹配算法进行局部特征点的匹配,提出了一种双向搜索的匹配策略来提取具有较强鲁棒性的特征点;然后,利用随机抽样一致算法进一步筛选所选定的特征点,并将保留下来的精确匹配特征点带入仿射运动模型求出全局运动矢量;最后,提取全局运动矢量中的抖动参数,并对原始图像进行补偿。实验结果表明,该方法可以快速有效地处理图像序列的仿射运动,水平和垂直方向的精确度小于1 pixel,并且具有较好的鲁棒性,可用于动载体摄像系统。     

计及运动副间隙的双曲柄六杆压力机机构动力学仿真向量键合图法

针对计及运动副间隙的双曲柄六杆压力机机构动力学仿真问题,提出了相应的向量键合图法。基于修正非线性连续接触碰撞力的混合模型,推导出间隙运动副的相对碰撞速度向量方程。在此基础上,建立了可以更精确描述间隙运动副的向量键合图模型,具有通用性强、模块化的特点,便于嵌入到系统的向量键合图模型中。由机构运动副的约束关系,将各构件的向量键合图模型相互键接,建立了计及驱动电机、运动副间隙的双曲柄六杆压力机机构向量键合图模型。应用相应的方法,使机构向量键合图模型的贮能元件皆具有积分因果关系,实现了计及驱动电机、运动副间隙的双曲柄六杆压力机机构计算机建模及动力学仿真。在此基础上,分析了运动副间隙对压力机机构运动学及动力学性能的影响,验证了所述方法的可靠性及有效性。通过与无质量弹簧阻尼运动副间隙模型的计算对比,进一步表明该方法可以提高系统动力学仿真的精度及实用性。     

Guided Intra-Patch Smoothing Graph Filtering for Single-Image Denoising

Graph filtering is an important part of graph signal processing and a useful tool for image denoising. Existing graph filtering methods, such as adaptive weighted graph filtering (AWGF), focus on coefficient shrinkage strategies in a graph-frequency domain. However, they seldom consider the image attributes in their graph-filtering procedure. Consequently, the denoising performance of graph filtering is barely comparable with that of other state-of-the-art denoising methods. To fully exploit the image attributes, we propose a guided intra-patch smoothing AWGF (AWGF-GPS) method for single-image denoising. Unlike AWGF, which employs graph topology on patches, AWGF-GPS learns the topology of superpixels by introducing the pixel smoothing attribute of a patch. This operation forces the restored pixels to smoothly evolve in local areas, where both intra- and inter-patch relationships of the image are utilized during patch restoration. Meanwhile, a guided-patch regularizer is incorporated into AWGF-GPS. The guided patch is obtained in advance using a maximum-a-posteriori probability estimator. Because the guided patch is considered as a sketch of a denoised patch, AWGF-GPS can effectively supervise patch restoration during graph filtering to increase the reliability of the denoised patch. Experiments demonstrate that the AWGF-GPS method suitably rebuilds denoising images. It outperforms most state-of-the-art single-image denoising methods and is competitive with certain deep-learning methods. In particular, it has the advantage of managing images with significant noise.     

多种遥感信息光化学复合模型研究

信息复合是遥感技术应用的前沿．是遥感图像处理方法的新内容。信息复合的目的，在于充分利用各种遥感信息资料，实现对各种信息数据的更新补充以及动态分析研究。本大根据国家自然科学基金项目“基于信息分析的遥感图像光化学处理系统的研究”的内容．着重阐述多种遥感信息光化学复合机理，并以成功的实例论述各种遥感信息源以及遥感信息源与非途感信息源的复合方法和复合效应。研究表明，多种遥感信息光化学复合实际上就是建立不用计算机的信息数据库的方法，其在遥感地学分析中具有广泛的实用意义。     

Self-consistent way to determine relative distortion of axial symmetric lens systems

We present a simple method to determine the relative distortion of axially symmetric lens systems. This method uses graphs to determine every parametric value instead of nonlinear minimization computation and is composed of an LCD screen to display a square grid pattern of pixel-wide spots and a set of analyzing processes for the spots in the image. The two Cartesian components of the spot locations are processed by a two-step linear least-square fitting to third-order polynomials. The graphs for the coefficients enable us to determine the amount of decentering of the camera lens axis with respect to the center of the image array and the tip/tilt of the screen, which in turn gives the relative distortion coefficient. We present experimental results to demonstrate the utility of the method by comparing our results with the corresponding values determined by open source software available online.     

Sequences of regressions and their independences

Ordered sequences of univariate or multivariate regressions provide statistical models for analysing data from randomized, possibly sequential interventions, from cohort or multi-wave panel studies, but also from cross-sectional or retrospective studies. Conditional independences are captured by what we name regression graphs, provided the generated distribution shares some properties with a joint Gaussian distribution. Regression graphs extend purely directed, acyclic graphs by two types of undirected graph, one type for components of joint responses and the other for components of the context vector variable. We review the special features and the history of regression graphs, prove criteria for Markov equivalence and discuss the notion of a?simpler statistical covering model. Knowledge of Markov equivalence provides alternative interpretations of a given sequence of regressions, is essential for machine learning strategies and permits to use the simple graphical criteria of regression graphs on graphs for which the corresponding criteria are in general more complex. Under the known conditions that a Markov equivalent directed acyclic graph exists for any given regression graph, we give a polynomial time algorithm to find one such graph.     

Modelling of spatial causality among distinctive properties of an image using conditional random field for image classification

In this paper, we proposed an ordered patch-based method using conditional random field (CRF) in order to encode local properties and their spatial relationship in the images to address texture classification, face recognition and scene classification problems. Typical image classification approaches classify images without considering spatial causality among distinctive properties of an image to represent it in the feature space. In this method first, each image is encoded as a sequence of ordered patches including local properties. Second, the sequence of these ordered patches is modelled as a probabilistic feature vector using CRF to model spatial relationship of these local properties; and finally, image classification is performed on such probabilistic image representation. Experimental results on several standard image datasets indicate that the proposed method outperforms some of existing image classification methods.     

基于图的半监督学习的遮挡边界检测方法

提出了一种基于图的半监督学习检测深度图像中遮挡边界的方法。该方法首先获取已标记的像素点和待检测深度图像中的像素点作为顶点构建连通无向图,其次提取无向图中各像素点的最大深度差特征和八邻域有效深度差之和特征组成特征向量,根据像素点的特征向量计算无向图中顶点之间的相似性并将该相似性作为无向图中对应边的权值,然后根据图的半监督学习思想判断无向图中待检测像素点是否为遮挡边界点,最后可视化遮挡边界点得到深度图像中的遮挡边界。实验结果表明,所提方法尽管只需少量的标记样本,但在准确性上却同已有基于监督学习的方法相当。     

部分逆M矩阵2-弦图的完备问题

本文采用图论的方法对任意阶部分逆M矩阵,当其对应的图为2-弦图时,研究了其逆M矩阵的完备问题。给出了完备定理以及具体完备的算法。     

Combinatorial optimization of special graphs for nodal ordering and graph partitioning

There are numerous applications of graph theory and algebraic graph theory in combinatorial optimization and optimal structural analysis. In this paper, a new canonical form as well as its relation with four structural models often encountered in practice and their corresponding graphs are presented. Furthermore, the block diagonalization of this form, which is performed using three Kronecker products and unsymmetric matrices, is studied. This block diagonalization leads to an efficient method for the eigensolution of adjacency and Laplacian matrices of special graphs. The eigenvalues and eigenvectors are used for efficient nodal ordering and partitioning of large structural models. The present method is far more simple than any existing general approach.     

基于有向图的工程变更传播分析的研究

论文提出了基于有向图的工程变更传播分析方法;开发了采用该方法进行工程变更分析的软件系统;分析了工程变更中零件变更的传播、协调、吸收和控制等主要问题;提出了传播模图和传播实图的概念;阐述了传播模图的数据结构、生成算法和使用它引导工程变更分析的过程。该文用传播实图记录零件变更的传播范围及各个变更零件的变更计划与影响评估;提出了案例的建立和重用方法,促进历史变更经验使用。使用这种方法和系统,可以使工程变更分析与评估更加严密、高效。