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11.
Traditional methods of extracting the ocean wave eddy information from remotely sensed imagery mainly use the edge detection technology such as Canny and Hough operators. However, due to the complexities of ocean eddies and image itself, it is sometimes difficult to successfully detect ocean eddies using these methods. A mnltifractal filtering technology is proposed for extraction of ocean eddies and demonstrated using NASA MODIS, SeaWiFS and NOAA satellite data set in the typical area, such as ocean west boundary current. Results showed that the new method has a superior performance over the traditional methods.  相似文献   
12.
Contamination of seismic reflection records at early times by first-order water reverberations can be especially severe during survey operations over hard and flat sea floors on the continental shelf or in lake environments. A new dereverberation scheme based on two classical techniques — predictive deconvolution and velocity filtering — has been developed to address this problem. The techniques are combined spatially to take advantage of their complementary offset- and time-dependent properties. Stage I of the scheme consists of applying predictive deconvolution at short offset. The data are previously conditioned by a normal moveout correction with the water velocity which restores the periodicity of the reverberations in the offset-time plane and enhances the performance of deconvolution. Stage II of the scheme involves velocity filtering in the common-midpoint domain which is particularly effective at long offset where the moveout difference between primary reflections and reverberations is largest. The dereverberation scheme is well suited for the initial processing of large volumes of data due to the general availability of cost-effective deconvolution and velocity filtering algorithms in seismic processing software packages. Practical implementation issues are illustrated by a field example from the GLIMPCE survey in Lake Superior.Lithoprobe Publication No. 475.  相似文献   
13.
一种改进的基于坡度变化的机载激光雷达点云滤波方法   总被引:2,自引:0,他引:2  
机载激光点云数据滤波是获取高精度数字表面模型和数字高程模型的关键。本文分析了几种重要的滤波算法,在研究基于坡度变化的滤波算法的基础上,提出一种改进的分块滤波处理的方法。实验表明:该方法能有效对点云数据进行分类。  相似文献   
14.
平面约束条件在LIDAR点云滤波中的应用   总被引:1,自引:1,他引:0  
介绍了一种利用平面约束条件对LIDAR点云数据进行滤波的方法,利用每个数据点的邻域点拟合平面,根据平面约束条件和平面点分类方法得到地面点,最后利用地面点内插该区域的DTM.  相似文献   
15.
提出了基于坡度对陡坡林区LIDAR点云数据滤波的预处理算法,结合迭代最小二乘滤波方法改进了滤波效果,实测数据表明,有效地降低了第一类误差和第二类误差。  相似文献   
16.
Income distribution dynamics and cross-region convergence in Europe   总被引:3,自引:3,他引:0  
This paper presents a continuous version of the model of distribution dynamics to analyse the transition dynamics and implied long-run behaviour of the EU-27 NUTS-2 regions over the period 1995–2003. It departs from previous research in two respects: first, by introducing kernel estimation and three-dimensional stacked conditional density plots as well as highest density regions plots for the visualisation of the transition function, based on Hyndman et al. (J Comput Graph Stat 5(4):315–336, 1996), and second, by combining Getis’ spatial filtering view with kernel estimation to explicitly account for the spatial dimension of the growth process. The results of the analysis indicate a very slow catching-up of the poorest regions with the richer ones, a process of shifting away of a small group of very rich regions, and highlight the importance of geography in understanding regional income distribution dynamics.
Manfred M. FischerEmail:
  相似文献   
17.
有色噪声作用下的卡尔曼滤波   总被引:2,自引:0,他引:2  
利用GPS载波相位三差观测量进行动态定位(或精密导航),就必须研究有色噪声滤波的理论问题.根据需求,推导了动态噪声、观测噪声为有色噪声的线性系统滤波公式,并证明白噪声卡尔曼滤波是有色噪声卡尔曼滤波的特例,或者说有色噪声的卡尔曼滤波是白噪声卡尔曼滤波的推广.  相似文献   
18.
用褶积滤波处理井水位对固体潮响应的滞后   总被引:2,自引:1,他引:1  
张昭栋  高玉斌 《地震》1993,(4):23-29
本文给出了一种用褶积滤波处理井水位对固体潮响应滞后的新方法。鲁07井水位观测资料用这种方法处理比一般回归方法的平均中误差少4.6mm。文中讨论了褶积滤波积分区间长度与水井含水层渗透系数的关系及褶积滤波比别尔采夫滤波的优越性。  相似文献   
19.
1983年菏泽5.9级地震前后沂水泉氡的变化   总被引:1,自引:0,他引:1  
沂水泉位于山东省沂水一汤头断裂带上。多年来的观测分析表明,影响沂水泉氡值变化的最大干扰是降雨。由于这种干扰存在着“记忆”滞后影响,所以用一般的相关分析难以将这种影响排除干净。本文对最小二乘法为建立模型的判据,用动态灰箱分析法拟合并推估观测系统的变化。在分析中用了四个状态变量:长趋势成分L(t)、年周期变化成分P(t)、降雨影响部分R(t)和随机变化部分S(t)。经过分析表明,沂水泉氡的长趋势部分1  相似文献   
20.
Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (Xn, n 0) or (Xt, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Yn, n 0) or (Yt, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.  相似文献   
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