Medical image contrast enhancement based on improved sparrow search algorithm

The collection or transmission of medical images is often disturbed by various factors, such as insufficient brightness and noise pollution, which will result in the deterioration of image quality and significantly affect the clinical diagnosis. To improve the quality of medical images, a contrast enhancement method based on improved sparrow search algorithm is proposed in this paper. The method is divided into two steps to enhance the medical images. First, a new transform function is introduced to improve the brightness or contrast of medical images, and two parameters in the transform function are optimized by the improved sparrow search algorithm. Second, adaptive histogram equalization method with contrast limited is used to equalize the result image of the previous step to make the pixel distribution of the image more uniform. Finally, a large number of experiments and qualitative and quantitative analyses were conducted on the common data sets. The analysis results demonstrate that the presented approach outperforms some existing medical image processing approaches.     

A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction

We analyze a variational approach to image segmentation that is based on a strictly convex non-quadratic cost functional. The smoothness term combines a standard first-order measure for image regions with a total-variation based measure for signal transitions. Accordingly, the costs associated with discontinuities are given by the length of level lines and local image contrast. For real images, this provides a reasonable approximation of the variational model of Mumford and Shah that has been suggested as a generic approach to image segmentation.The global properties of the convex variational model are favorable to applications: Uniqueness of the solution, continuous dependence of the solution on both data and parameters, consistent and efficient numerical approximation of the solution with the FEM-method.Various global and local properties of the convex variational model are analyzed and illustrated with numerical examples. Apart from the favorable global properties, the approach is shown to provide a sound mathematical model of a useful locally adaptive smoothing process. A comparison is carried out with results of a region-growing technique related to the Mumford-Shah model.     

Computing the Kantorovich Distance for Images

Computing the Kantorovich distance for images is equivalent to solving a very large transportation problem. The cost-function of this transportation problem depends on which distance-function one uses to measure distances between pixels.In this paper we present an algorithm, with a computational complexity of roughly order (N2), where N is equal to the number of pixels in the two images, in case the underlying distance-function is the L1-metric, an approximation of the L2-metric or the square of the L2-metric; a standard algorithm would have a computational complexity of order (N3). The algorithm is based on the classical primal-dual algorithm.The algorithm also gives rise to a transportation plan from one image to the other and we also show how this transportation plan can be used for interpolation and possibly also for compression and discrimination.     

电力有源滤波器控制器的研究与仿真分析

建立了包括有源电力滤波器（ＡＰＦ）在内的公共连接点（ＰＣＣ）的数学模型;针对实际控制器计算过程中的时间延迟,提出对负载电流值进行预测的两种算法,对逆变器的开关元件提出一种新型脉宽调制（ＰＷＭ）控制方案,并采用电力电子仿真软件包进行了仿真验证。     

一种快速自适应谱估计算法

通过对梯度格型快速自适应算法的研究,结合最大熵谱外推目前存在的缺点,将梯度格型算法应用于最大熵谱外推中,并将其与伯格算法进行了比较。     

动态优化调度走向实用的策略与段落全局优化

本文在总结动态优化调度在实际系统中应用经验的基础上,提出了动态优化调度走向实用的策略及以段落一局优化算动态化调度的方法,该策略可以较地贯彻电力系统运行“安全,优质,经济”的原则,段落全局优化方法则可以一次性处理各种负荷紧段落,包括单调升降段落及以往方法只有通过反向导引才能够处理的陡升连续等类的段落,具有计算时间短,节省内存等特点,为动态优化调度在电力系统中的进一步实用化打下了坚实的基础。     

PWM逆变器的一种神经网络控制方法

提出一种用于ＰＷＭ逆变器控制的神经网络控制器、通过仿真和实验研究表明,这种基于动态ＢＰ神经网络的控制器可以使逆变器获得较好的动、静态特性、并且对电源、负载扰动有较强的适应能力。     

区域与特征相结合的立体匹配算法

基于区域的匹配算法是立体匹配中常用的方法之一,而基于特征的匹配算法能解决区域匹配中遇到的某些问题,根据特征匹配与区域匹配的特点,提出了一种特征匹配与区域匹配相结合的立体匹配算法.首先在特征匹配中通过改进的Harris提取角点并结合单调性约束和惟一性约束进行匹配,特征匹配的结果能减少误匹配率,为区域匹配打下了基础.然后在...     

Web应用日志分析系统分析与设计

互联网的蓬勃发展为生活、学习、工作提供了诸多便利,但随之而来的网络安全隐患日趋明显.应用日志分析作为一种重要的信息安全保障措施,有效地弥补了传统安全防御技术的缺陷.主要分析了传统日志分析的常用方法,并在此基础上,提出了一种新的日志读取方法和模式匹配算法.通过测试表明,这些改进对提高日志的分析效率起到了积极效果.     

跨站脚本攻击模式研究

文章对将包含XSS攻击代码的HTTP URLs单词集合分为两部分。按一定粒度分词,运用Apriori算法挖掘攻击模式字符串频繁项集,并在此基础上运用类似Apriori算法思想的PrioriMerge子串合并算法得到攻击模式并统计其频率,实验结果表明算法能有效地挖掘出XSS攻击模式。