云底高度的激光云高仪、红外测云仪以及云雷达观测比对分析

为了比较几种自动化测云仪器的性能,中国气象局气象探测中心在南京信息工程大学的气象探测基地首次组织了一次为期近5个月的比对试验,试验仪器包括四台激光云高仪、两部红外测云仪、一台全天空成像仪以及一部毫米波云雷达。对其中大部分仪器取得的三个月云底高度数据进行了初步的分析,结果表明：三台激光云高仪测量结果比较一致;两部红外测云仪在测量低云时一致性稍差;云雷达与激光云高仪测量的最低层云底高度数据一致性较差,但与红外测云仪的测量结果匹配较好。     

可见光/红外全天空成像仪和云雷达联合反演云高

为解决大部分设备无法单独获取全天空云底高度的问题,基于中国气象局大气探测基地可见光/红外天空成像仪和毫米波云雷达2019年6月的灰度值与云底高度数据,利用辐射传输模式计算地面8～14μm波段向下红外辐射随天顶角的变化关系,并根据红外波段测得的天顶云底灰度值与非天顶位置的天顶角余弦灰度值之间的线性关系,从而反演得到全天空云底高度。结果表明：(1)相比于全天无云的情形,在一天的相同时间时,全天有云时的天顶灰度值较高。(2)当云底高度为2000 m以上且云层较厚时,云底高与红外模块所测灰度值的相关性明显好于云层较薄的低云。(3) 2019年8月12日的个例验证结果显示,反演云高与通过云雷达测得的实际云高相关系数为0.956,而与取天顶附近约30°天顶角得到的云高相关系数为0.9508。     

一种遥感图像中的道路检测方法

道路是遥感图像的重要特征。提出一种从遥感图像中检测道路目标的方法。首先,进行图像预处理,提取边缘,然后进行图像分块并利用Hough变换进行道路检测。分析了Hough变换的特点,并研究了Hough变换域极值点参数的特点,改进了Hough变换在道路目标检测中的应用。该方法不仅快速地检测机场等严格的线状道路目标,而且对具有一定曲率的道路目标同样有效。     

机载LiDAR点云中电力线的提取和重建研究

为了实现输电线走廊的有效监管，采用了一种基于机载激光雷达(LiDAR)点云的电力线提取和重建的方法。首先利用点云的回波信息滤除大部分地物点，保留电力线的全部信息, 然后基于格网高差和高程阈值剔除大部分非电力线点云，实现电力线的初提取。针对初步提取出的电力线点云，通过Hough变换分离出单根输电线点。为提高电力线点的提取精度，对Hough变换提取的结果进行了改进，利用局部极值点检测的方法确定杆塔的位置，最后通过带有限制条件的多项式模型对每档电力线进行分段拟合，实现电力线模型的3维重建。结果表明，利用该算法提取出了424个电力线点，总的提取精度达到87.603%，拟合出的电力线模型效果较好。该算法可以自动、精确地实现LiDAR点云数据中电力线的提取和重建，对输电线走廊巡检具有很好的实用价值。     

Classification of sets of mixed pixels with the hypothesis-testingHough transform

A new method is presented for mixed pixel classification where the classification of groups of mixed pixels is achieved by using the hypothesis-testing Hough transform. The motivation of the work is that some other estimation methods based on robust statistics, such as the standard Hough transform, have been criticised that, although they can cope with the presence of outliers, they give poor performance in the absence of outliers in comparison to the least-squares-error method. The method proposed in the paper is demonstrated using simulated data and proved to perform equally well in the presence and in the absence of outliers. It is also applied to real Landsat TM data     

Rectangular building extraction from stereoscopic airborne Radar images

From the recent availability of images recorded by synthetic aperture radar (SAR) airborne systems, automatic results of digital elevation models (DEMs) on urban structures have been published lately. This paper deals with automatic extraction of three-dimensional (3-D) buildings from stereoscopic high-resolution images recorded by the SAR airborne RAMSES sensor from the French Aerospace Research Center (ONERA). On these images, roofs are not very textured whereas typical strong L-shaped echoes are visible. These returns generally result from dihedral corners between ground and structures. They provide a part of the building footprints and the ground altitude, but not the building heights. Thus, we present an adapted processing scheme in two steps. First is stereoscopic structure extraction from L-shaped echoes. Buildings are detected on each image using the Hough transform. Then they are recognized during a stereoscopic refinement stage based on a criterion optimization. Second, is height measurement. As most of previous extracted footprints indicate the ground altitude, building heights are found by monoscopic and stereoscopic measures. Between structures, ground altitudes are obtained by a dense matching process. Experiments are performed on images representing an industrial area. Results are compared with a ground truth. Advantages and limitations of the method are brought out.     

复杂背景下基于Hough变换的人脸定位

提出一种在复杂背景下人脸快速定位的方法。对复杂背景下的人脸图像提取边缘之后，先用基于“上半圆”的Hough变换初步检测到人脸的大致位置，然后在圆附近再用基于“上半椭圆”的Hough变换快速定位出人脸。实验证明了本方法的有效性。     

一种改进的Hough变换提取圆的方法

本文提出了一种基于方向可变滤波器的改进Hough变换方法。该方法首先利用方向可变滤波器检测出图像边缘以及边缘的方向特性,然后基于边缘点及其方向,通过改进的Hougll变换得到圆心、半径。最后,将该算法应用于球类对象分割并得到较好的结果。     

An empirically based path loss model for wireless channels insuburban environments

We present a statistical path loss model derived from 1.9 GHz experimental data collected across the United States in 95 existing macrocells. The model is for suburban areas, and it distinguishes between different terrain categories. Moreover, it applies to distances and base antenna heights not well-covered by existing models. The characterization used is a linear curve fitting the decibel path loss to the decibel-distance, with a Gaussian random variation about that curve due to shadow fading. The slope of the linear curve (corresponding to the path loss exponent, γ) is shown to be a random variate from one macrocell to another, as is the standard deviation σ of the shadow fading. These two parameters are statistically modeled, with the dependencies on base antenna height and terrain category made explicit. The resulting path loss model applies to base antenna heights from 10 to 80 m, base-to-terminal distances from 0.1 to 8 km, and three distinct terrain categories     

方向自适应的星载光子计数激光测高植被冠层高度估算

星载光子计数激光测高系统具有较高的沿轨距离分辨率,能够探测得到植被冠层和地表的连续高程信息。然而星载植被点云的低点云密度和低信噪比,对植被相对冠层高度的估算方法提出了新的要求。本文提出了一种方向自适应的星载光子计数激光测高植被点云冠高估算方法。首先通过寻找点云高程统计直方图中代表冠层和地面位置的极值进行粗去噪,大致得到信号高程所在的范围,并估算出冠层,地面和噪声点云的平均密度以及地表坡度。随后对粗去噪后的点云进行方向自适应的密度聚类精去噪,其邻域的方向为地表坡度,与密度有关的阈值均根据估算出的点云密度自适应的做出调整。在滤波后,结合点云的密度和高程百分比分别找出地面与树冠顶端的初始点,并通过三角网方法(TIN)扩展初始点以进行分类,最终确定地表与树冠顶端的高程。采用ATLAS星载激光测高仪的植被点云对算法进行了验证,结果表明算法能够正确估算植被冠高,十分适用于坡度较大和叶面积指数较低的地区,其中冠顶与地面的高程和机载LIDAR数据高程的决定系数R~2分别为0.99与0.77,均方根误差RMSE为0.28 m与2.6 m。     

基于哈夫变换的图像边缘连接

图像边缘的检测可以得到图像中处于边缘上的像素点,由于受到噪声等干扰,一组边缘像素很少能完整地描绘一条边缘。利用哈夫(Hough)变换可以将边缘像素连接成有意义的边缘。现有文献对哈夫变换在极坐标中的应用,存在不同的形式和论述,容易造成概念混淆。详细叙述哈夫变换的基本原理,及在直线检测中的应用。尤其是对极坐标下直线的标准方程,进行详细地推导和论述,从而对哈夫变换的应用进行有益的补充。     

The discrete wavelet transform and the scale analysis of thesurface properties of sea ice

The formalism of the one-dimensional discrete wavelet transform (DWT) based on Daubechies wavelet filters is outlined in terms of finite vectors and matrices. Both the scale-dependent wavelet variance and wavelet covariance are considered and confidence intervals for each are determined. The variance estimates are more accurately determined with a maximal-overlap version of the wavelet transform. The properties of several Daubechies wavelet filters and the associated basis vectors are discussed. Both the Mallat orthogonal-pyramid algorithm for determining the DWT and a pyramid algorithm for determining the maximal-overlap version of the transform are presented in terms of finite vectors. As an example, the authors investigate the scales of variability of the surface temperature and albedo of spring pack ice in the Beaufort Sea. The data analyzed are from individual lines of a Landsat TM image (25-m sample interval) and include both reflective (channel 3, 30-m resolution) and thermal (channel 6, 120-m resolution) data. The wavelet variance and covariance estimates are presented and more than half of the variance is accounted for by scales of less than 800 m. A wavelet-based technique for enhancing the lower-resolution thermal data using the reflected data is introduced. The simulated effects of poor instrument resolution on the estimated lead number density and the mean lead width are investigated using a wavelet-based smooth of the observations     

Accelerated Hough transform using rectangular image decomposition

A novel fast method for evaluating the Hough transform is proposed, which can be used to accelerate detection of prevalent linear formations in binary images. An image is decomposed using rectangular blocks and the contribution of each whole block to the Hough transform space is evaluated, rather than the contribution of each image point. The resulting acceleration in the calculation of the Hough transform field is demonstrated in two image processing experiments related to object axis identification and skew detection of digitised documents     

遥感图像中无水桥梁识别新算法

 给出了边缘密度和线段复杂度的定义,并提出一种遥感图像中无水桥梁的识别新算法.首先对图像进行边缘提取,计算像素点的边缘密度,根据边缘密度进行图像分割,接着采用Hough变换提取直线,利用线段复杂度等确定疑似桥梁区域,然后计算疑似桥梁区域像素点的纹理特征,并构成一个特征矢量,最后将此特征矢量送入BPNN进行分类,统计该区域所有像素点的分类结果以判决是否属于桥梁.实验结果表明,该算法能够较好地识别出遥感图像中的无水桥梁目标.     

一种快速高效的Hough变换并行算法

本文提出了一种基于流水光总线可重构线性阵列(LARPBS)模型的快速高效Hough变换算法.该算法利用LARPBS有力的通讯功能和计算能力,对直线上的黑色象素进行抽取和统计.对于大小为n×n的二值数字图象、m个θ参数值,本算法可以使用mn²个处理机在O(1)时间完成,从而使速度和效率都达到最优.文中还给出当LARPBS中处理机个数少于mn²时的算法分解执行方法,说明算法具有很好的可扩放性.     

基于卫星红外窗区数据的云顶高度反演方法

云顶高度是云最基本且十分重要的参数,同时也是研究空域容量、航线高度配备和天气预测预警等的重要参数。简单描述了基于卫星资料反演云顶高度的主要方法的原理和优缺点,然后介绍了单红外窗区法、太阳光反射率-红外窗区法、H2O-红外窗区法和红外分裂窗查算表算法的原理和优缺点,并对相关卫星的业务算法进行了简要评述。接着对单红外窗区法反演对流云云顶高度进行了检验。结果表明,单红外窗区法反演不透明厚云的精度和相关性都很高。最后分析了影响各方法精度的原因,并对后续云顶高度反演方法进行了展望。     

Operational retrieval of cloud-top heights using MISR data

Due to its unique nine-angle configuration, the Multi-angle Imaging SpectroRadiometer (MISR) can retrieve cloud parameters such as cloud-motion vectors and cloud-top heights using a purely geometrical technique that involves locating the same cloud features at different viewing angles. The geometrical nature of this technique means that the retrievals are relatively insensitive to the absolute instrument calibration. Fast stereo-matching algorithms have been developed to perform this image matching automatically on an operational basis. Preliminary results are shown of the operational retrievals together with comparisons against other data. Cloud-top height is generally obtained on a 1.1-km grid with an accuracy of /spl plusmn/ 562 m, even over snow and ice. The limitations of the technique, resulting at times in height blunders, noisy retrievals, and discrete effects of wind correction, are discussed.     

Mixed pixel classification with robust statistics

The authors present a novel method for mixed pixel classification where the Hough transform and the trimmed means methods are used to classify small sets of pixels. They compare the performance of these methods with the least squares error method, and they show that in the presence of outliers, the trimmed means method is far more reliable than the traditional least squares error method, and even when no outliers are present, its performance is comparable to that of the least squares error method. The method is exhaustively tested using simulated data, and it is also applied to real Landsat TM data for which ground data are available     

基于随机森林算法的FY-4A云底高度估计方法

基于2017年8月至10月FY-4A的云顶高度、云光学性质等上游产品和A-Train系列卫星星载毫米波雷达和激光雷达主动探测的云底高度资料,利用随机森林算法建模,提出了FY-4A对最上层云云底高度的估计算法,并用2017年11月独立样本对算法进行了检验与评估.结果表明,该算法可以有效实现对最上层云云底高度的估计,与星载主动探测结果相比,平均绝对偏差为1. 29 km,相关系数为0. 80.对单层云的估计结果相对较好,而多层云存在时云底高度的估计结果一般偏小.     

SBDART对云地面长波辐射强迫的模拟研究

为了研究云的地面长波辐射强迫与云的关系,利用SBDART辐射传输模式模拟了云量、云底高和云光学厚度对云的地面长波辐射强迫的影响,并对国内外学者研究的云的地面长波辐射强迫随云量变化的非线性原因进行了理论分析.结果表明:对相同的云,在不同的大气条件下,地面长波辐射强迫是不同的;云的地面长波辐射强迫随云量的增大而增大,随云底高的增大而减小,随云光学厚度的增大而增大,当光学厚度大于10以后,几乎不再增大.随云量的增加,低云和光学厚度大的云出现概率增大,是云的地面长波辐射强迫随云量变化呈非线性的两个原因.