Three points method for searching the best least absolute deviations plane

In this paper a new method for estimation of optimal parameters of a best least absolute deviations plane is proposed, which is based on the fact that there always exists a best least absolute deviations plane passing through at least three different data points. The proposed method leads to a solution in finitely many steps. Moreover, a modification of the aforementioned method is proposed that is especially adjusted to the case of a large number of data and the need to estimate parameters in real time. Both methods are illustrated by numerical examples on the basis of simulated data and by one practical example from the field of robotics.     

基于小波变换的图像去噪方法的研究

小波变换能有效的去除高斯噪声,中值滤波能有效的去除脉冲噪声,两者结合可以更有效的去除高斯噪声和脉冲噪声的混合噪声.当医学图像去除混合噪声时,先进行中值滤波再进行小波去噪的方法优于先进行小波去噪后再进行中值滤波的方法,且去噪后图像视觉效果较好,而且图像均方误差(M SE)也较小.在图像去噪处理中这种方法具有实际应用价值.     

Robust regression techniques A useful alternative for the detection of outlier data in chemical analysis

The validation of an analytical procedure means the evaluation of some performance criteria such as accuracy, sensitivity, linear range, capability of detection, selectivity, calibration curve, etc. This implies the use of different statistical methodologies, some of them related with statistical regression techniques, which may be robust or not. The presence of outlier data has a significant effect on the determination of sensitivity, linear range or capability of detection amongst others, when these figures of merit are evaluated with non-robust methodologies.In this paper some of the robust methods used for calibration in analytical chemistry are reviewed: the Huber M-estimator; the Andrews, Tukey and Welsh GM-estimators; the fuzzy estimators; the constrained M-estimators, CM; the least trimmed squares, LTS. The paper also shows that the mathematical properties of the least median squares (LMS) regression can be of great interest in the detection of outlier data in chemical analysis. A comparative analysis is made of the results obtained by applying these regression methods to synthetic and real data. There is also a review of some applications where this robust regression works in a suitable and simple way that proves very useful to secure an objective detection of outliers. The use of a robust regression is recommended in ISO 5725-5.     

基于中值滤波和提升小波分析的图像去噪方法研究

针对现有算法大多对单一高斯噪声或脉冲噪声进行图像滤波的问题,在对二维图像平滑去噪的过程中,采用基于中值滤波和提升小波变换相结合的图像去噪方法。在中值滤波基础上,构造基于脉冲检测的中值滤波器,找出混合噪声中脉冲噪声并进行滤波;与此同时,对原始小波进行提升,构造提升小波,然后采用提升小波阈值去噪方法抑制高斯噪声。实验结果表明:采用本文方法,混合噪声得到有效抑制,去噪效果好。     

一种新的改进Canny图像边缘检测算法

针对传统的Canny算法在平滑滤波时对图像边缘检测的影响,以及需要预先设定高低阈值等缺点,本文提出了一种新的Canny边缘检测算法。首先采用自适应中值滤波对图像进行处理;其次,添加45°和135°方向的梯度模板来计算梯度幅值;最后,采用Otsu算法计算经梯度幅值运算得到图像的高低阈值。实验结果表明,该改进的Canny算法具有良好的抗噪性能,并且能精确的检测出边缘信息。     

基于改进的分块压缩感知红外图像重建

针对基于压缩感知理论的红外图像重建问题,提出一种基于改进的分块压缩感知红外图像重建方法。该方法首先对原始红外图像进行分块,并对每个子块用相同的观测矩阵进行随机观测,获得少量的观测数据;然后利用谱图小波变换优异的稀疏特性,将其引入平滑投影Landweber算法进行迭代优化重建,同时采用混合中值滤波进行处理以增加图像的平滑度和减少块伪影,最后输出满足要求的高质量红外图像。实验结果表明,在相同采样率下,该方法对于不同类型红外图像的重建性能均优于目前广为采用的一些小波压缩感知方法,可获得更高质量的红外图像。     

δ修正Cramr-von Mises检验的非无偏性(英文)

在简单假设下,证明了对任意给定水平α∈(0,1)和样本容量n,δ修正Cramr-von Mises检验的非无偏性.     

一种新的运动自适应去隔行算法

提出基于棱边方向检测的运动自适应去隔行算法,该算法能充分利用图像序列的时间和空间上的相关信息,采用新颖的相邻场运动检测方法区分视频序列中的运动和静止部分.对于运动部分,使用改进的基于棱边方向的边沿自适应插值算法;对于静止部分,采用三点中值滤波插值算法.仿真实验表明：算法无论在画面视觉效果还是视频图像信噪比,均达到良好了效果.     

区间图上可带负权的2-中位选址问题

本文研究了区间图上可带负权的2-中位选址问题.根据目标函数的不同,可带负权的$p-$中位选址问题($p\geq 2$)可分为两类：即 MWD 和 WMD 模型;前者是所有顶点与服务该顶点的设施之间的最小权重距离之和,后者是所有顶点与相应设施之间的权重最小距离之和.在本篇论文中,我们讨论了区间图上可带负权2-中位选址问题的两类模型,并分别设计时间复杂度为$O(n^2)$的多项式时间算法.     

MOBVE分布参数的估计及其改进

本文讨论由Marshall和Olkin引进的二元指数分布(MOBVE分布)的参数估计问题.这个分布关于某个控制测度的密度函数被提出.对于边缘分布相同的情形,本文给出了充分统计量并讨论了它的性质;对两个参数各提出了一个无偏估计并采用协方差改进法分别对其作了改进.