真实感图形生成的加速技术研究及实现

引入了一种直线与三角形求交的简洁算法和区域块投影算法,有效地减少了真实感图形生成中光线与物体的求交计算时间.另外,采用区别对待高光区域和非高光区域等方法,解决了Gouraud浓淡算法不能生成高光效果的问题,改善了图形质量.     

任意曲面求交问题综述

曲面求交是ＣＡＤ／ＣＡＭ领域中最重要也最为复杂的问题之一，它是曲面造型中各种几何处理的关键。本文就已有的任意曲面求交算法进行了系统地分析与评价，指出了目前所存在的问题。     

求第K棵树形图的算法

本文利用拟阵交的交错序列思想，并借助改进的求第ｋ最短路的算法，给出了求第ｋ最小树形图的算法，时间复杂度为Ｏ（ｋ３｜Ａ｜３）．     

关于Corley求所有有效生成树算法的修正

Ｃｏｒｌｅｙ在（１）中提出了一个求所有有效生成树的算法。但是此算法得到的最终解含有许多非有效的生成树。本文修改了Ｃｏｒｌｅｙ算法，提出并证明一个子树是有效生成树的子树的两个必要条件，根据这个结果，我们建立了一个修正算法并证明了它的有效性，同时，Ｃｏｒｌｅｙ算法的缺点被克服了。     

关于求线性规划初始可行基的生成算法

本文用反例证明了文「１」提出的求线性规划寝可行基的生成算法有错误,并给出了修正的生成算法。     

最小度生成树的一种近似算法

最小度生成树问题是一个NP难问题.本文给出了求最小度生成树的一种近似算法,这种算法得到的生成树的度数比最优解至多大1.     

次限制拟阵基的排序算法

§1 引言本文对一般的拟阵,给出在一个子集上具有次限制所有拟阵基的排序算法。著名的“greedy”算法是求连通图最小权的支撑树的好算法。在连通图上特别指定了一个顶点,求在该顶点次限制的最小权的支撑树,Glover—Klingman也给出了好算法。Burns—Haff给出了图的支撑树权的大小进行排序的生成算法,并且指出能够把它推广为拟阵基的排序算法。本文对一般的拟阵,给出在一个集上具次限制的所有拟阵基的按权的大小进行排序的生成算法。     

无限维Hillbert空间中单调变分不等式解的近似迭代算法

在无穷维Hillbert空间中研究了一类单调型变分不等式，把求单调型变分不等式解的问题转化为求强单调变分不等式的解，建立了一种新的迭代算法，并证明了由算法生成的迭代序列强收敛于单调变分不等式的解，从而推广了所列文献中的许多重要结果．     

多幅图像恢复有高光和阴影物体的三维表面

提出一种在多光源下多幅图像来恢复有高光和阴影物体三维表面的方法.对有高光和阴影图片恢复物体的三维表面,物体表面可以认为是L am bertian模型加上高光阴影区域的混合模型.     

交轨法求轨迹方程

交轨法即轨迹交点法之简称.它是平面几何中常用的作图方法之一.我们借用交轨法的基本思想,在平面解析几何里,求一些第三类型轨迹问题的轨迹方程,颇为见效. 交轨法的基本思想是什么呢?我们知道,一个动点在平面上生成的轨迹,是该动点满足某些     

Fast algorithm for geometrical coding of digital images

A fast algorithm for geometrical coding is presented in the paper. It allows one to perform the image analysis by methods of differential geometry rather than widespread methods based on gradient and Hessian calculations. Nowadays, one of the most important aspects in image analysis is the speed of computations. The algorithm for geometrical coding is comparable or faster than traditional algorithms of image analysis and in many cases it gives better results. Several examples of algorithm working results for contour detection are presented.     

An accelerated algebraic multigrid algorithm for total-variation denoising

The variational partial differential equation (PDE) approach for image denoising restoration leads to PDEs with nonlinear and highly non-smooth coefficients. Such PDEs present convergence difficulties for standard multigrid methods. Recent work on algebraic multigrid methods (AMGs) has shown that robustness can be achieved in general but AMGs are well known to be expensive to apply. This paper proposes an accelerated algebraic multigrid algorithm that offers fast speed as well as robustness for image PDEs. Experiments are shown to demonstrate the improvements obtained.     

MEA-BP模型在遥感影像分类中的应用研究

遥感影像分类作为遥感技术的一个重要应用,对遥感技术的发展具有重要作用.针对遥感影像数据特点,在目前的非线性研究方法中主要用到的是BP神经网络模型.但是BP神经网络模型存在对初始权阈值敏感、易陷入局部极小值和收敛速度慢的问题.因此,为了提高模型遥感影像分类精度,提出采用MEA-BP模型进行遥感影像数据分类.首先采用思维进化算法代替BP神经网络算法进行初始寻优,再用改进BP算法对优化的网络模型权阈值进一步精确优化,随后建立基于思维进化算法的BP神经网络分类模型,并将其应用到遥感影像数据分类研究中.仿真结果表明,新模型有效提高了遥感影像分类准确性,为遥感影像分类提出了一种新的方法,具有广泛研究价值.     

An efficient self-adaptive model for chaotic image encryption algorithm

In this paper, an efficient self-adaptive model for chaotic image encryption algorithm is proposed. With the help of the classical structure of permutation-diffusion and double simple two-dimensional chaotic systems, an efficient and fast encryption algorithm is designed. However, different from most of the existing methods which are found insecure upon chosen-plaintext or known-plaintext attack in the process of permutation or diffusion, the keystream generated in both operations of our method is dependent on the plain-image. Therefore, different plain-images will have different keystreams in both processes even just only a bit is changed in the plain-image. This design can solve the problem of fixed chaotic sequence produced by the same initial conditions but for different images. Moreover, the operation speed is high because complex mathematical methods, such as Runge–Kutta method, of solving the high-dimensional partial differential equations are avoided. Numerical experiments show that the proposed self-adaptive method can well resist against chosen-plaintext and known-plaintext attacks, and has high security and efficiency.     

Design of an image encryption scheme based on a multiple chaotic map

In order to solve the problem that chaos is degenerated in limited computer precision and Cat map is the small key space, this paper presents a chaotic map based on topological conjugacy and the chaotic characteristics are proved by Devaney definition. In order to produce a large key space, a Cat map named block Cat map is also designed for permutation process based on multiple-dimensional chaotic maps. The image encryption algorithm is based on permutation–substitution, and each key is controlled by different chaotic maps. The entropy analysis, differential analysis, weak-keys analysis, statistical analysis, cipher random analysis, and cipher sensibility analysis depending on key and plaintext are introduced to test the security of the new image encryption scheme. Through the comparison to the proposed scheme with AES, DES and Logistic encryption methods, we come to the conclusion that the image encryption method solves the problem of low precision of one dimensional chaotic function and has higher speed and higher security.     

基于混合单纯形算法的模糊均值图像分割

针对模糊C均值算法用于图像分割时对初始值敏感、容易陷入局部极值的问题,提出基于混合单纯形算法的模糊均值图像分割算法.算法利用Nelder-Mead单纯形算法计算量小、搜索速度快和粒子群算法自适应能力强、具有较好的全局搜索能力的特点,将混合单纯形算法的结果作为模糊C均值算法的输入,并将其用于图像分割.实验结果表明:基于混合单纯形算法的模糊均值图像分割算法在改善图像分割质量的同时,提高了算法的运行速度.     

Restoration of images based on subspace optimization accelerating augmented Lagrangian approach

We propose a new fast algorithm for solving a TV-based image restoration problem. Our approach is based on merging subspace optimization methods into an augmented Lagrangian method. The proposed algorithm can be seen as a variant of the ALM (Augmented Lagrangian Method), and the convergence properties are analyzed from a DRS (Douglas-Rachford splitting) viewpoint. Experiments on a set of image restoration benchmark problems show that the proposed algorithm is a strong contender for the current state of the art methods.     

Convergence analysis of tight framelet approach for missing data recovery

How to recover missing data from an incomplete samples is a fundamental problem in mathematics and it has wide range of applications in image analysis and processing. Although many existing methods, e.g. various data smoothing methods and PDE approaches, are available in the literature, there is always a need to find new methods leading to the best solution according to various cost functionals. In this paper, we propose an iterative algorithm based on tight framelets for image recovery from incomplete observed data. The algorithm is motivated from our framelet algorithm used in high-resolution image reconstruction and it exploits the redundance in tight framelet systems. We prove the convergence of the algorithm and also give its convergence factor. Furthermore, we derive the minimization properties of the algorithm and explore the roles of the redundancy of tight framelet systems. As an illustration of the effectiveness of the algorithm, we give an application of it in impulse noise removal.     

A novel image encryption algorithm based on a 3D chaotic map

Recently [Solak E, Çokal C, Yildiz OT Biyikogˇlu T. Cryptanalysis of Fridrich’s chaotic image encryption. Int J Bifur Chaos 2010;20:1405-1413] cryptanalyzed the chaotic image encryption algorithm of [Fridrich J. Symmetric ciphers based on two-dimensional chaotic maps. Int J Bifur Chaos 1998;8(6):1259-1284], which was considered a benchmark for measuring security of many image encryption algorithms. This attack can also be applied to other encryption algorithms that have a structure similar to Fridrich’s algorithm, such as that of [Chen G, Mao Y, Chui, C. A symmetric image encryption scheme based on 3D chaotic cat maps. Chaos Soliton Fract 2004;21:749-761]. In this paper, we suggest a novel image encryption algorithm based on a three dimensional (3D) chaotic map that can defeat the aforementioned attack among other existing attacks. The design of the proposed algorithm is simple and efficient, and based on three phases which provide the necessary properties for a secure image encryption algorithm including the confusion and diffusion properties. In phase I, the image pixels are shuffled according to a search rule based on the 3D chaotic map. In phases II and III, 3D chaotic maps are used to scramble shuffled pixels through mixing and masking rules, respectively. Simulation results show that the suggested algorithm satisfies the required performance tests such as high level security, large key space and acceptable encryption speed. These characteristics make it a suitable candidate for use in cryptographic applications.     

Quasi-human seniority-order algorithm for unequal circles packing

In the existing methods for solving unequal circles packing problems, the initial configuration is given arbitrarily or randomly, but the impact of different initial configurations for existing packing algorithm to the speed of existing packing algorithm solving unequal circles packing problems is very large. The quasi-human seniority-order algorithm proposed in this paper can generate a better initial configuration for existing packing algorithm to accelerate the speed of existing packing algorithm solving unequal circles packing problems. In experiments, the quasi-human seniority-order algorithm is applied to generate better initial configurations for quasi-physical elasticity methods to solve the unequal circles packing problems, and the experimental results show that the proposed quasi-human seniority-order algorithm can greatly improve the speed of solving the problem.