搜索空间逐步平滑技术的分析与应用

系统分析了搜索空间逐步平滑策略的可行性.在离散的情况下,分析了搜索空间逐步平滑法在离散问题中的应用,并与没有经过平滑技术处理过的遗传算法的运行过程进行了比较,得出搜索空间逐步平滑法收敛效率更高.     

参数化CAD中参数有效范围的算法研究

为了解决在参数化CAD系统中由于参数赋值不合理而导致的几何实体重建失败的问题,提出了确定一类二维参数化CAD模型中参数有效范围的代数算法。该算法可以实时求解所有简单多边形中距离约束参数的有效取值范围,并利用几何变换简化求解规模,提高求解效率。研究结果表明,该算法提供的有效取值范围内的任一赋值,均可保证重建后几何实体的拓扑形状不发生改变,在一定程度上提高了参数化CAD软件的设计效率和人机交互的智能化水平。同时对算法复杂度进行了分析,该算法的复杂度为O(n~2)。     

Global parameterization of a topological surface defined as a collection of trimmed bi‐parametric patches: Application to automatic mesh construction

We describe a new geometric algorithm to map surfaces into a plane convex area. The mapping transformation is bijective; it redefines the whole surface as a unique bi‐parametric patch. Thus this mapping provides a global parametrization of the surface. The surfaces are issued from industrial CAD software; they are usually described by a large number of patches and there are many shortcomings. Indeed, the decomposition into patches depends on the algorithm of the geometric modelling system used for design and usually has no meaning for any technological application. Moreover, in many cases, the surface definition is not compatible, i.e. patches are not well connected, some patches are self‐intersecting or intersect each other. Many applications are hard to address because of these defects. In this paper we show how patch‐independent meshing techniques may be easily automated using a unique metric in a plane parametric space. Thus we provide an automatic procedure to build valid meshes over free‐form surfaces issued from industrial CAD software (Computer Aided Design: this terminology should refer to a large amount of software. For the scope of this paper we only refer to geometric modelling systems. Indeed geometric modelling systems remain the kernel of many CAD software). Copyright © 2002 John Wiley & Sons, Ltd.     

Solving general field equations in infinite domains with dual reciprocity boundary element method

The dual reciprocity boundary element method has been successfully employed to solve general field equations posed in a closed domain, i.e. interior problems. Up to now, however, little effort has been made to extend it to exterior problems (i.e. general field equations posed in an infinite region), which are commonly encountered in engineering practice. In this paper, the interpolation functions associated with exterior problems, which were proposed by Loeffler and Mansur (in Boundary Elements X, Vol. 2, Springer, 1988), are first examined. We have found that the choice of the arbitrary constant, the inclusion of which is necessary in those interpolation functions, has clear effects on the accuracy of the numerical results. A mapping transformation, through which any exterior problem can be solved by solving an equivalent interior problem, is then proposed. Although there are certain regularity conditions attached to such a mapping, they can be easily satisfied if the unknown function satisfies certain regularity conditions at infinity in the original exterior problem. A successful application of this mapping transformation to a transient heat transfer problem demonstrates the good performance of this approach.     

图像镶嵌技术理论、难点及应用

图像镶嵌技术是一种表示图象序列信息的新技术，它通过找出一对图象间的视觉相关性，进而求出图象间的转换关系，最终将一序列真实图象合成为同一世界坐标系下的全维场景。这里，我们给出图象镶嵌技术的基本理论，然后讨论图象镶嵌技术的难点及应用。     

Residual spatial entropy-based image contrast enhancement and gradient-based relative contrast measurement

This paper proposes a novel algorithm to achieve both global and local contrast enhancement using a new definition of residual spatial entropy of gray levels of an image. Residual spatial entropy is utilized to assign a weight to each gray level which is further used in mapping of input gray levels to output gray levels to achieve global contrast enhancement. A non-linear mapping is applied on transform-domain coefficients of image enhanced globally to perform local contrast enhancement. The algorithm allows to control levels of perceived global and local contrast. New definitions of full-reference relative contrast measures are also introduced. Experimental results show that proposed algorithm produces better or comparable contrast-enhanced images than several state-of-the-art algorithms.     

基于图像尺寸变换的角点检测算法研究

为了研究基于尺寸变换的角点检测技术的检测效果,基于图像缩小法的角点检测技术,提出了图像放大法的角点检测技术。详细介绍了两种检测技术的计算原理并进行了实验验证,结果表明这两种方法都是行之有效的。在此基础上,将这两种方法与不进行图像尺寸变换的角点检测技术进行了对比研究,结果表明,基于尺寸变换的角点检测技术与不进行图像尺寸变化的角点检测技术的检测结果精度基本相同,因此,在角点的实际检测计算中,无需对被检测图像进行尺寸变换处理。     

Invariants under image perspective transformations: Theory and examples

The objective of this work is to develop automated techniques for recognizing the same objects in images that differ in scale, tilt, and rotation. Such perspective transformations of images are produced when aerial images of the same scene are taken from different vantage points. The algebraic methods developed previously do not utilize the intensity values of the images, i.e., their pixel gray levels. Since image features essential for object recognition, such as edges and local image textures, may be described in terms of derivatives and integrals of the image intensity, it is necessary to investigate whether certain differential and integral operators applied to different perspective views of the same object are also invariant under the perspective transformation. We proceed to derive new differential operators and their corresponding integral invariants for curves and planar objects. We introduce a variant form of Fourier expansion specially adapted to the projective transformation. Extensions to three dimensions are discussed, as well as applications to other image formation models such as synthetic aperture radar (SAR). These results are steps toward a computational model for perspective-independent object recognition.     

Model-Based Clustering of Nonparametric Weighted Networks With Application to Water Pollution Analysis

Abstract

Water pollution is a major global environmental problem, and it poses a great environmental risk to public health and biological diversity. This work is motivated by assessing the potential environmental threat of coal mining through increased sulfate concentrations in river networks, which do not belong to any simple parametric distribution. However, existing network models mainly focus on binary or discrete networks and weighted networks with known parametric weight distributions. We propose a principled nonparametric weighted network model based on exponential-family random graph models and local likelihood estimation, and study its model-based clustering with application to large-scale water pollution network analysis. We do not require any parametric distribution assumption on network weights. The proposed method greatly extends the methodology and applicability of statistical network models. Furthermore, it is scalable to large and complex networks in large-scale environmental studies. The power of our proposed methods is demonstrated in simulation studies and a real application to sulfate pollution network analysis in Ohio watershed located in Pennsylvania, United States.     

On computational methods for variational inequalities

In this note, we focus on optimised mesh design for the Finite Element (FE) method for variational inequalities using global norm estimates for local error control. The strategies are based on the so called dual-weighted-residual (DWR) approach to a posteriori error control for FE-schemes (see, e.g., Rannacher et al. [19, 6, 2]), where error control for the primal problem is established by solving an auxiliary (dual) problem. In this context we blamed (cf. e.g., Rannacher and Suttmeier [18, 19]) global norm estimates being not that useful in applications. But having a closer look at the DWR-concept, one observes that in fact global (energy) error bounds can be employed to establish local error control. Our ideas and techniques are illustrated at the socalled obstacle problem.It turns out, that reliable and efficient energy error control is one main ingredient to establish useful a posteriori error bounds for local quantities. Therefore, in addition, we derive an unified approach to a posteriori error control in the energy norm for elliptic variational inequalities of first kind. Eventually, this framework is applied to Signorinis problem.     

用于移动机器人遥操作的数字图象稳定化技术研究

提出了基于长时运动滤波和图象仿射变换的数字图象稳定模型，在ＰＩＰＥ机上完成了一个数字图象的实时稳定系统。关键技术包括图象运动检测方法、运动滤波方法，消除抖动的运动补偿方法以及从色素到象素的图象校正算法。     

Reducing the computational cost of local search in the hybrid evolutionary algorithm with application to electronic imaging

This article focuses on the efficiency problems associated with the use of local search in the hybrid evolutionary algorithm. A two-phase cyclic local search is proposed that alternates the random search and the downhill simplex method (DSM), and helps prevent the algorithm from converging to a sub-optimal solution in multidimensional optimization. The algorithm utilizes a novel micro-model of image local response, in order to reduce the number of fitness evaluations during the local DSM search, with the application to the global optimization problem arising in electronic imaging. The problem is stated as the search for the feasible transformation parameters that minimize the difference between two images. Image local response is defined as the variation of the fitness function that occurs because of a small variation of the parameters, and is computed over a small pixel area. The computed response coefficients specify a contraction transformation applied to the vector of the regular DSM coefficients that control the movement and the shape of the simplex. The transformation adjusts the length of the vector, making the step size of the simplex adaptive to the local properties of the fitness landscape. The computational experiments with two-dimensional grayscale images provide the experimental support and justification of the analytical model of image local response and its utilization for the reduction of the computational cost of local search, without the loss of the quality of the final solution.     

Difference Detection Between Two Images for Image Monitoring

In manufacturing industries, images are commonly used for quality control purposes. In such applications, if the quality of the products is good, then their images should be all similar to the image of a good-quality product. Therefore, comparison of images is a fundamental task in image-based quality control. This problem, however, is complicated in the sense that (1) observed images often contain noise, and (2) the related images need to be geometrically matched up first because images of different products could be geometrically mismatched because the relative positions between a camera and different products are often not exactly the same. The first issue requires a statistical method that can remove noise, and the second issue is related to the so-called image registration problem in the image processing literature. In this article, we propose effective methods for detecting difference between two images of products, and our proposed methods can accommodate both noise and geometric mismatch mentioned above. Theoretical results and numerical examples show that they can work effectively in applications.     

分块特征匹配与局部差分结合的运动目标检测

针对摄像机在运动情况下运动目标检测问题的研究,提出了一种尺度不变特征变换图像分块特征匹配和局部差分算法相结合的运动目标检测方法。该方法不仅可以减少图像配准参数求解所需要的时间,弥补全局运动补偿对图像完整性的影响,并且可以在摄像机运动的情况下准确地检测出运动目标。 实验证明了该方案的有效性。     

基于可拓论的不相容问题求解研究

以单特征不相容问题及其解变换的研究为基础,探讨多特征不相容问题的结构、判断方法和求解方法,并以在市场营销中的应用为例说明其应用价值。这一研究将为矛盾问题的智能化处理提供新的工具。     

A GLCM-Feature-Based Approach for Reversible Image Transformation

Recently, a reversible image transformation (RIT) technology that transforms a secret image to a freely-selected target image is proposed. It not only can generate a stego-image that looks similar to the target image, but also can recover the secret image without any loss. It also has been proved to be very useful in image content protection and reversible data hiding in encrypted images. However, the standard deviation (SD) is selected as the only feature during the matching of the secret and target image blocks in RIT methods, the matching result is not so good and needs to be further improved since the distributions of SDs of the two images may be not very similar. Therefore, this paper proposes a Gray level co-occurrence matrix (GLCM) based approach for reversible image transformation, in which, an effective feature extraction algorithm is utilized to increase the accuracy of blocks matching for improving the visual quality of transformed image, while the auxiliary information, which is utilized to record the transformation parameters, is not increased. Thus, the visual quality of the stego-image should be improved. Experimental results also show that the root mean square of stego-image can be reduced by 4.24% compared with the previous method.     

Structure constrained image completion by geometric transformation model and dynamic patches

Image completion aims to fill in a damaged region (hole) using texture form known regions. In this study, a novel image completion method is proposed that can repair a hole region using preserved structure. A geometric transformation model is first proposed to determine the relation between patches. Then, a multi-layer dynamic patch solution is obtained that can both effectively recover damaged structure and expedite the algorithm. To obtain satisfactory results, image completion is reduced to an energy optimization problem. An objective function is established, and the optimal solution is obtained. The proposed method is applied in various scenes, and the results demonstrate that this method has strong potential as an image completion technique.     

基于邻域重构模型的高分辨SAR图像精确配准

合成孔径雷达(SAR)的成像过程使其高分辨图像的几何形变呈现局部性.针对高分辨SAR图像精确配准问题,本文提出一种基于邻域重构模型的局部转换函数.邻域重构模型首先采用重构系数刻画参考图像中每个像素点的几何位置;接着给出了一种重构控制点的选择标准使每个像素的配准误差达到最小;最后根据重构系数及控制点坐标对输入图像进行再抽样以实现配准.与经典分片线性映射相比,该模型从理论上给出了一种区域剖分准则:对于每个像素选取能使配准误差能达到最小的控制点作为重构控制点.对模拟数据和真实SAR图像进行了试验,结果表明,该模型能有效地提高配准精度.     

基于塔形分解的局部熵差图像配准

以图像局部熵差为匹配准则,确定关键点的匹配位置。逐点计算图像局部熵,将图像局部熵序列进行塔式分解。采用金字塔式的数据结构,通过从低分辨率图像开始模板匹配,找出粗匹配点,逐步找到原始图像(即高分辨率图像)的精确匹配点,大大减少了计算量。该算法具有良好的抗噪声能力和抗几何失真能力。实验结果表明,当实时图相对于参考图旋转不超过5°时,正确匹配达到76%以上;当椒盐噪声强度不超过5%时,正确匹配达到78%以上;当零均值高斯白噪声方差不超过0.02时,正确匹配达到70%以上。     

A comparison study of the LMAPS method and the LDQ method for time-dependent problems

This paper compares numerical solutions of spatial-temporal partial differential equations based on two RBF-based meshless methods: the local method of approximate particular solutions (LMAPS) and the local RBFs-based DQ method (LDQ). To avoid the ill-conditioned problems of the global version, the weighting coefficients at the supporting points are determined by solving low-order linear systems instead of large dense linear systems. The Runge–Kutta method is adopted for time stepping schemes. The numerical experiments have shown that the LMPAS method and the LDQ method are capable of solving the initial boundary value problem for spatial-temporal partial differential equations with high accuracy and efficiency.