一种获取图像区域最小外接矩形的算法及实现

给出了二值数字图像区域外接矩形的一种获取算法。对于图像方形点阵中的8近邻的情形，建立了标定区域边界的基本圈，通过自动标定区域边界取得其像素点集，最后培出了获取图像区域最小外按矩形的实现方法。     

点阵多孔金属夹芯板振动特性分析及优化设计

采用空间桁架结构分析的网架结构连续化方法对点阵多孔金属夹芯板的夹芯层桁架进行了连续化处理,即,将夹芯层桁架等效为连续介质,并分别推导了金字塔型、四面体型、kagome型和4杆型点阵多孔金属夹芯板的抗弯刚度和等效剪切刚度．然后,应用分解刚度法推导了四边简支条件下点阵多孔金属夹芯板的固有振动频率公式,并与有限元计算结果进行了对比,表明所得公式具有较高的精度．最后,研究了夹芯板单胞结构尺寸对固有振动频率的影响,以夹芯层高度和桁架杆截面尺寸为设计变量,以第一阶频率最大化为目标对夹芯板进行了优化,优化后的夹芯板振动频率得到了明显提高．     

矩形非均匀采样算法和对数级坐标变换算法的比较分析

针对对数极坐标变换引起的图像周边模糊和图像细节丢失等现象，提出了矩形非均匀采样方法。图像中心采样区的大小可根据实际需要进行选取，对其进行均匀采样，对周边区进行分层均匀采样，随距采样中心距离的增大，采样率逐渐降低。对矩形非均匀采样、经典LPT和变参数LPT三者的运算量进行了比较，总体上说，矩形方法具有最少的运算量，而且可以克服对数极坐标变换图像的扭曲，并便于硬件实现。     

基于图形几何特征相似度的点阵比较

在工程实践中，需要从具有多个相似点阵的已知点阵（Spot Array）集[S]中匹配出一个与未知点阵[P]最相似的点阵[P*]，然后对两个点阵做样本点匹配。完成这个任务的关键挑战在于如何匹配出与未知点阵[P]最相似的已知点阵[P*]。这个问题比较新颖，目前少有理论研究，文中探索出一种基于图形的几何特征分析的描述算法，算法首先将每个点阵构建成一个唯一的简单图（Simple Graph）轮廓图形，同时为每个图形构建一个链式结构，然后利用轮廓图形的几何特征计算未知点阵与各已知点阵的相似程度，匹配出相似度最高的一个，最后利用链式结构完成两个点阵间的样本点匹配。该算法不受点阵的坐标系旋转和尺度缩放的影响。通过实验表明，该算法能够快速、准确地完成点阵相似度比较和样本点匹配任务。     

单片机系统汉字及图形点阵的实现

对图像及采集的数据进行显示，是单片机系统重要的功能之一。要显示图像及汉字，必须得到对应的点阵信息。本文详细阐述了图像及汉字点阵的生成方法。     

大型点阵图形的打印输出技术：算法与实现

打印图形点阵的规模取决于打印缓冲区的大小．最终局限于主机的内存容量．本文提出了几种大型点阵图形打印的实用技术：动态内存管理技术、ＥＭＳ和ＸＭＳ技术、文件Ｉ／Ｏ技术和内存覆盖技术；给出了相应的实现程序；分析比较了它们各自的优点和缺点；最后指出了采用内存覆盖技术实现对多路信号进行连续监测以及对某些高频暂态信号进行快速打印再现的可能性．     

对抗网络数字图像混合噪声滤除算法仿真

为了提高数字图像混合噪声滤除算法的滤除效果,设计了对抗网络数字图像混合噪声滤除算法.首先对对抗网络数字图像边缘进行了检测,在虚拟现实技术下并对图像进行了预处理,将图像按照等间距形式进行采样,然后判断图像中的混合噪声,标记窗口像素,最后采用小波阈值算法对对抗网络数字图像噪声进行滤除,结合虚拟现实技术重构有效低频信号的小波系数和阈值高频信号系数,得到混合噪声滤除后的新图像,实现对抗网络数字图像混合噪声滤除.实验结果表明,经过上述研究的对抗网络数字图像混合噪声滤除算法的均方误差低,峰值信噪比与结构相似度都较高,取得了较好的应用效果.     

点阵汉字无级变倍算法

本文给出了由一种汉字字库得到任意大小汉字点阵的算法.该算法能对任意二值点阵图像进行放大平滑.简单放大是按字节进行运算,速度快;最佳平滑操作不是对简单放大后的点阵按位操作,而是根据原点阵的特性,在需要平滑的地方进行操作,需操作的位数不会超过图像总点数的5％.用该方法输出的汉字质量和速度都令人满意.     

基于新阈值函数和小波分析的数字图像去噪方法

在数字图像处理过程中消除和减弱噪声对信号具有很重要的影响。中值滤波是传统的减少图像噪声,提高图像质量的可行方法。文章研究了中值滤波及其改进算法在图像去噪中的应用,基于小波分析基础理论和数字图像信号的小波变换分解重构原理,通过对小波分解系数选定恰当的阈值并进行阈值量化,基于小波分解后的高低频系数进行信号重构,从而有效去除或降低信号的噪声。本文采取的算法在MATLAB仿真平台进行了验证,结果表明,基于本文提出的阈值函数和小波分析处理方法对图像去噪具有更好的适应性,能够更好的改善数字图像的质量。     

汉字点阵无级压缩的优化算法

本文给出一优化的无级压缩变换算法, 可将宋体、楷体、黑体、仿宋体的48x48点阵汉字无级压缩为48点阵以下的任意点阵, 且压缩变换后的点阵结构完整, 字中相应笔划粗细均匀, 字形美观。     

Computer graphics on a hexagonal grid

Aberrations in digital images can be attenuated by computing the image at higher-than-display resolution, convolving it with a two-dimensional filter kernel and decimating the filtered image back to display resolution for presentation. Traditionally, this has been performed using a rectangular sampling grid, which is parallel to the display scan direction. In this paper, the application of a hexagonal sampling grid is proposed. Rectangular and hexagonal processing are discussed, and it is shown that despite the differences in their mathematical bases, their algorithmic implementations are similar. A series of test patterns are presented and evaluated. It is concluded that hexagonal processing results in a greater reduction in aliasing in regions of vertical/near vertical features of images than is achieved by rectangular processing, without any degradation in other regions, and with negligible additional computational effort.     

Edge detection in a hexagonal-image processing framework

With processing power of computers and capabilities of graphics devices increasing rapidly, the time is ripe to reconsider using hexagonal sampling for computer vision in earnest. This paper reports on an investigation of edge detection in the context of hexagonally sampled images. It presents a complete framework for processing hexagonally sampled images which addresses four key aspects: conversion of square to hexagonally sampled images, storage, processing, and display of these images. Results from using edge detection on this framework show that (a) the computational requirement for processing a hexagonally sampled image is less than that for square sampled images, and (b) a better qualitative performance which is due to the compact and circular nature of the hexagonal lattice. This last point needs to be exploited in the development of edge detectors for hexagonally sampled images.     

Resampling on a Pseudohexagonal Grid

This paper investigates resampling techniques on a pseudohexagonal grid. Hexagonal grids are known to be advantageous in many respects for sampling and representing digital images in various computer vision and graphics applications. Currently, a real hexagonal grid device is still difficult to find. A good alternative for obtaining the advantages of a hexagonal grid is to construct a pseudohexagonal grid on a regular rectangular grid device. In this paper we first describe the options and procedures for constructing such a pseudo-hexagonal grid and then demonstrate techniques of resampling digital images on the pseudohexagonal grid. Four distinct resampling kernels are tested, and their results are illustrated and compared.     

Measuring and Improving Image Resolution by Adaptation of the Reciprocal Cell

Traditionally, discrete images are assumed to be sampled on a square grid and from a special kind of band-limited continuous image, namely one whose Fourier spectrum is contained within the rectangular reciprocal cell associated with the sampling grid. With such a simplistic model, resolution is just given by the distance between sample points.Whereas this model matches to some extent the characteristics of traditional acquisition systems, it doesn't explain aliasing problems, and it is no longer valid for certain modern ones, where the sensors may show a heavily anisotropic transfer function, and may be located on a non-square (in most cases hexagonal) grid.In this work we first summarize the generalizations of Fourier theory and of Shannon's sampling theorem, that are needed for such acquisition devices. Then we explore its consequences: (i) A new way of measuring the effective resolution of an image acquisition system; (ii) A more accurate way of restoring the original image which is represented by the samples. We show on a series of synthetic and real images, how the proposed methods make a better use of the information present in the samples, since they may drastically reduce the amount of aliasing with respect to traditional methods. Finally we show how in combination with Total Variation minimization, the proposed methods can be used to extrapolate the Fourier spectrum in a reasonable manner, visually increasing image resolution.     

基于高斯抽样算法的NTRU类数字签名方案

针对NTRU类数字签名方案的签名值会泄露私钥的部分信息等问题,提出一种NTRU类数字签名方案。该方案通过私钥生成循环格,采用格上高斯抽样算法在此循环格上找出与杂凑后消息最近的向量作为消息的签名值。与现有的方案相比,该方案在保持签名和验证过程效率的同时,安全性方面具有2个新的性质：(1)由公钥伪造签名的困难性是基于循环格上的最近向量问题;(2)由新方案生成的大量签名值在空间分布呈球形,不泄露私钥的任何信息。     

Triangular Bernstein moment-based identification of algebraic curves

Extending our previous results, in this paper we present a theoretical improvement of a strategy for the identification of binary images with algebraic boundaries. Such identification is obtained from few samples and it is based on a representation of the image shape in terms of non-separable bivariate Bernstein polynomials piecewisely defined over triangular domains.     

双目系统全视域采样的SVM标定模型分析

目的 为改善摄像机间接标定采样不全、模型表达模糊问题,实现小视场下检测视域完备采样,提出一种基于双目系统全视域采样的支持向量机（SVM）标定方法。方法 该方法利用六角晶格标定板靶点序号可读特点为基础,采集整个双目系统有效视域中检测点的视差坐标、世界坐标并建立完备的样本集。选取SVM对该样本集进行训练,将SVM算法得到的模型参数代入其决策函数中进行求解,获得公式化的标定模型。由于六角晶格标定板的四角和中心分布了5个互为非中心对称的多边形,可在标定板部分区域被采集的情况下获取标定板位姿信息,进而读取采集的各靶点序号。通过上下移动标定板,利用HALCON算子获取图像中各靶点的序号,建立双目视觉系统检测区域的完备样本集。最后,利用SVM算法训练样本获得标定模型,可以明确表达出标定模型的数学形式。结果 与传统采样建立的模型进行对比分析,实验结果表明该方法建立模型的标定误差减小了24.51%,降低了标定模型在传统方法未采样区域的标定误差,证明了该方法的可行性。结论 提出一种基于双目系统全视域采样的支持向量机标定方法,通过非中心对称的多边形确定标定板上靶点的序号,实现双目视觉系统检测视域的完备采样。实验结果表明该方法提高了摄像机间接标定的精度,具有良好的适用性和鲁棒性,适用于小视域内双目视觉系统的间接标定。     

基于矩形编码的抖动半调图像无损压缩算法

结合有序抖动图像具有周期性块状纹理的特性,提出一种基于矩形编码的抖动半调图像无损压缩算法.针对半调图像黑自像素交替频繁的现象,根据抖动模板的大小等间隔抽取对应图像块上的像素进行下采样,使采样后的子图具有成片的黑白区域.对黑白子图进行行异或运算,通过矩形划分的编码方法实现无损压缩.实验结果表明,该算法的压缩效率较高.     

基于混沌和SVD DWT的稳健数字图像水印算法*

针对现有适用于图像的数字水印对信号处理和几何失真比较敏感的问题,提出一种稳健的数字图像水印算法。该算法先对整个图像应用三级离散小波变换,再对低频域运用奇异值分解,并通过修改奇异值,嵌入经过混沌置乱的水印图像的奇异值,在小波变换域的中频系数上嵌入水印信息。水印检测时,分别在中频区域和低频提取水印并进行比较,采用效果较好的水印作为检测水印。实验结果表明,该方法对一般的信号处理操作及几何攻击等均具有较好的鲁棒性。     

六边形稀疏网格上的FFT算法

稀疏网格是一种具有特殊分层插值性质的非均匀网格形式,稀疏网格上的离散傅立叶变换算法称为Hyperbolic Cross FFT算法.这一算法能够有效降低采样点数量,并将指数时间复杂度的d维DFT算法降低到O(Nlog^dN)^[10].六边形网格是另一种具有特殊性质的网格,具有在采样点数量较少和采样效率较高等优势.本文的研究工作主要集中在将六边形网格和稀疏网格相结合,构造六边形稀疏网格上的FFT算法.通过定义六边形和方形网格下标之间的转换,实现了六边形稀疏网格上的FFT算法,并通过数值实验证明了这一算法的有效性.