台风中心的旋转定位

台风在大气中绕着自己的中心急速旋转、同时又向前移动的空气涡旋。由于台风中心集中了台风绝大部分的能量和含水量,也是台风破坏力集中的地方,因为台风中心的定位对于台风路径预测和灾害预报来说都是非常重要的。传统的台风中心定位方式精度底,误差大,难以满足实际需要。为了准确地进行台风中心的定位,根据台风卫星云图的数字化特征和台风运动规律,提出了旋转定位方式。它的理论基础是,根据运动学和台风学原理,台风虽然是非刚性物体,但是其中心部分可相对看成是刚体的运动,因为热带气旋中心具有转动矢零的特点。这样,在卫星云图序列动画中,找出前后两次相应特征点的轨迹,即可算出其中的转动原点,也就是转动矢量为零的点。由于该方法结合了云图特性和运动因素,因而提高了精度和合理性。由此可见,对于台风这样的运动物体,结合其运动特征的中心定位法是台风中心定位的必然方向。     

基于遗传算法初始群体优化的台风中心自动定位

针对误差梯度求导方法求解台风中心自动定位最优目标函数时,具有解的局部优化问题以及最优解获取困难的不足,本文将遗传算法应用到卫星云图台风中心自动定位的优化求解中,实现了台风中心的准确自动定位。同时,考虑到标准遗传操作中初始群体的随机生成对最优解的搜索具有很强的敏感性和不确定性问题,本文根据台风云系的灰度分布特征,对初始群体的生成进行了改进与优化,求得了最优数值解。多个台风中心定位仿真试验结果验证了该方法的合理性和可靠性。     

台风云图伪彩色增强的Berkeley小波变换法

将Berkeley小波变换(BWT)和线性分配伪彩色增强方法相结合,给出一种有效的台风云图伪彩色增强方法。首先在Berkeley小波域增强云图的细节,然后将增强后的云图分别利用经典的线性分配和改进的线性分配法进行彩色增强。最后将所给出的方法与直接利用经典的线性分配方法、经典离散正交小波预处理后利用改进的线性分配方法进行对比分析。实验结果证明,该方法简便易行,运算量小,在应用中有较大的灵活性,为低对比度台风云图增强处理提供了一种新途径,同时能够有效突出台风眼区和外围螺旋云带等台风结构信息,为后续台风中心定位和台风强度预报提供参考。     

基于云导风场的形成期台风定位

研究形成期台风云图的普遍性规律,根据云图对象的特殊性对求取运动对象光流场的传统MCC(最大相关系数)算法进行改进,由此生成的云导风矢量图能够准确体现风场绕台风中心旋转这一客观事实.本文将云导风矢量与台风中心的关系归纳为台风定位判定规则,编制的定位算法对于各类形成期台风具有普遍适应性,定位结果较令人满意.     

基于FY-2C气象卫星云图的台风分割方法的研究

在利用FY-2C气象卫星云图进行台风中心自动定位与跟踪的研究中,台风云系的分割是处理中关键的一步。结合台风主体云系具有灰度值较高、面积较大、活动范围有限和像素集中的特点,综合采用阈值法、数学形态学法和数理统计等方法,对FY-2C气象卫星云图中的红外一通道兰勃托原始投影云图中的台风分割进行了研究,取得了满意的效果。     

台风中心定位中的螺旋线自动识别算法

本文是台风中心定位系统的核心算法，运用图象处理和模式识别技术进行云图螺旋线特征提取，得到有螺旋线特征的曲线段，最后运用曲线拟合技术进行螺旋线拟合定解决了台风中心定位依靠于工操作加工经验的判定方式而使台风预报准确偏低的问题，提高了台风预报的速度和精度。     

一种利用FY-2卫星数据的台风中心定位方法

针对台风监测中无眼台风的中心定位不够准确的问题,提出一种利用风云2(FY-2)卫星数据的可同时适用于有眼台风和无眼台风的自动台风中心定位方法。该方法首先计算FY-2卫星图像中每个点的梯度值;然后绘制梯度向量的平行线并计算交汇次数存入密度矩阵中,计算得到的密度矩阵中的最大值即为台风中心的初步估算位置;最后使用高斯滤波进行亮温修正进一步确定中心位置。通过分析多个发源于热带海面的台风,并与中国气象局(China Meteorological Administration,CMA)发布的最佳路径数据集以及其他方法进行比较,证明了所提方法能够准确地确定台风中心位置。该方法可以自动检测台风中心并能代替传统的人工定位方法。     

无眼台风自动定位方法研究

本文利用GMS红外云图对无眼有螺旋云带的台 风进行了自动定位研究,提出了由云图预处理、云图交互式分割、台风螺旋云带形态特征提 取、螺旋线拟合及定位的四步定位方案,取得了较好的效果．     

卫星云图有眼台风中心定位算法研究

本文分析和研究了单幅红外卫星云图台风定位问题,初步研究了有眼台风的模式识别,提出有眼区台风的中心定位算法.根据气象领域知识,眼区处在台风主体云系最大内切圆圆心附近,算法先提取出台风主体云系,应用数学形态学求取台风最大内切圆中心和半径,在此范围内寻找台风眼区.为了排除云洞和云缝的干扰,提出使用距离和灰度信息组成判别式求取台风眼区.实验证明具有较高的定位精度,能适合气象预报业务化的要求.     

基于纹理和区域特征的台风卫星云图分割方法

在利用GMS红外卫星云图进行无眼台风自动定位方法的研究中,台风云系的分割是处理中关键的一步,文章提出了一种基于纹理和区域特征的台风云系分割方法。首先利用图像的分形维数和灰度特征对台风云系中的密蔽云区进行有效的识别后,然后启动基于区域约束的区域生长计算得到台风云系。     

A novel nonlinear algorithm for typhoon cloud image enhancement

A novel nonlinear gray transform method is proposed to enhance the contrast of a typhoon cloud image. Generally, the typhoon cloud image obtained by a satellite cannot be directly used to make an accurate prediction of the typhoon’s center or intensity because the contrast of the received typhoon cloud image may be bad. Our aim is to extrude the typhoon’s eye in the typhoon cloud image. A normalized arc-tangent transformation operation is designed to enhance global contrast of the typhoon cloud image. Differential evolution algorithm is used to choose the optimal nonlinear transform parameter. Finally, geodesic activity contour model is used to extract the typhoon’s eye to verify the performance of the proposed method. Experimental results show that the proposed method can efficiently enhance the global contrast of the typhoon cloud image while greatly extruding the typhoon’s eye.     

Research on Typhoon Precipitation Retrieval Algorithm based on FY-3C MWHTS

In order to estimate the instantaneous precipitation rates brought by the typhoon, the Level 1 brightness temperatures from the Microwave Humidity and Temperature Sounder (MWHTS) onboard the FY-3C satellite and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 precipitation product data are used to retrieve the precipitation rates in the typhoon area using the multiple linear regression and BP neural network retrieval algorithms. The results show that the precipitation distribution maps retrieved by these two algorithms can be clearly observed the location, distribution and structural information of the typhoons such as typhoon center, cloud wall and spiral rain belt, which are consistent with the TMPA 3B42 precipitation product data. In addition, from a quantitative point of view, the TMPA 3B42 precipitation data and surface precipitation rate (mm/hr) retrieved by these two precipitation retrieval algorithms reach higher correlation and smaller deviations and root mean square errors, and the retrieval accuracy is higher. Therefore, these two retrieval algorithms can be used to retrieve the precipitation in the typhoon area. It also shows that microwave on-orbit observation data from the FY-3C MWHTS can play a high application value in typhoon monitoring and precipitation research.     

基于FY-3C MWHTS的台风降水反演算法研究

为估测台风带来的地表瞬时降雨率，利用FY-3C上搭载的微波湿温探测仪（Microwave Humidity and Temperature Sounder，MWHTS)的L1级在轨观测亮度温度数据与多卫星降水分析TMPA（Tropical Rainfall Measuring Mission（TRMM）Multi-Satellite Precipitation Analysis）3B42降水产品数据，通过多元线性回归和BP神经网络两种算法对台风区的降水情况进行了反演研究。结果表明，由这两种算法反演的降水分布图可以清晰地看到台风中心、云墙以及螺旋雨带等台风的位置、分布及结构信息，这与TMPA 3B42降水产品数据估测到的台风降水分布图相一致。此外，从定量的角度来看，TMPA 3B42降水数据与这两种反演算法反演的地表瞬时降水量（mm/hr）都具有较高的相关性和较小的偏差和均方根误差，反演的精度较高。故这两种算法都可以用来反演台风区的降水量，同时也表明FY-3C MWHTS微波在轨观测资料在台风区监测及降水研究中能发挥出较高的应用价值。     

Segmentation of typhoon cloud image by combining a discrete stationary wavelet transform with a continuous wavelet transform

An algorithm is proposed that employs a multi-threshold technique to segment a typhoon cloud image. For both reducing the noise and enhancing the detail in the typhoon cloud image, the noise is reduced by a Wiener filter and the detail is enhanced by a nonlinear gain operator in the discrete stationary wavelet domain in the proposed algorithm. Then, the histogram equalization technique is used to enhance the global contrast of the processed image. In order to reduce the false peaks of the histogram of the denoised and enhanced typhoon cloud image (DETCI), a Bezier curve is used to smooth the histogram. An optimal segmentation threshold is then obtained from the multiple thresholds obtained from the Bezier histogram. The optimal threshold is used to segment the DETCI. The region of the maximum area in the segmented DETCI is selected as a region of interest (ROI). Thus other objects of small cloud masses are removed by the above method. We replace the area of the ROI with the corresponding area of the original typhoon cloud image to obtain the segmented ROI (SROI). Again the Bezier histogram is used to smooth the false peaks in the histogram of the SROI. In order to detect accurately the peaks and valleys in the curve of the Bezier histogram, a continuous wavelet transform is used to determine the location of peaks and valleys. After the wavelet transform, multi-segmented images at different scales are obtained. A criterion is employed to select an optimal segmentation scale. Finally, the whole typhoon cloud series is segmented accurately by the proposed method. Experimental results show that the proposed algorithm can efficiently segment the typhoon cloud series from a typhoon cloud image, and is better than the Olivo and HQ methods for analysing the structure of the typhoon wind field.     

Contour curve reconstruction from cloud data for rapid prototyping

In this study, a method for generation of sectional contour curves directly from cloud point data is given. This method computes contour curves for rapid prototyping model generation via adaptive slicing, data points reducing and B-spline curve fitting. In this approach, first a cloud point data set is segmented along the component building direction to a number of layers. The points are projected to the mid-plane of the layer to form a 2-dimensional (2D) band of scattered points. These points are then utilized to construct a boundary curve. A number of points are picked up along the band and a B-spline curve is fitted. Then points are selected on the B-spline curve based on its discrete curvature. These are the points used as centers for generation of circles with a user-define radius to capture a piece of the scattered band. The geometric center of the points lying within these circles is treated as a control point for a B-spline curve fitting that represents a boundary contour curve. The advantage of this method is simplicity and insensitivity to common small inaccuracies. Two experimental results are included to demonstrate the effectiveness and applicability of the proposed method.     

基于扫描点云数据的零部件边缘轮廓提取技术

针对目前大型零部件边缘轮廓线提取效率低的问题,提出一种基于扫描点云数据的零部件边缘轮廓提取技术.该技术从边缘轮廓线的形成方式出发,通过分析边缘轮廓线垂直截面线的分布特征,定义了模式向量表征屋脊型和折线直线-直线相交型截面线.提取过程主要包含截面线数据的获取、截面线类型的识别和边缘轮廓线数据的提取这3个步骤.为获取边缘轮...