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1.
基于经验模态分解的高分辨率影像融合(英文) 总被引：3，自引：0，他引：3
High resolution image fusion is a significant focus in the field of image processing. A new image fusion model is presented based on the characteristic level of empirical mode decomposition （EMD）. The intensity hue saturation （IHS） transform of the multi-spectral image first gives the intensity image. Thereafter, the 2D EMD in terms of row-column extension of the 1D EMD model is used to decompose the detailed scale image and coarse scale image from the high-resolution band image and the intensity image. Finally, a fused intensity image is obtained by reconstruction with high frequency of the high-resolution image and low frequency of the intensity image and IHS inverse transform result in the fused image. After presenting the EMD principle, a multi-scale decomposition and reconstruction algorithm of 2D EMD is defined and a fusion technique scheme is advanced based on EMD. Panchromatic band and multi-spectral band 3,2,1 of Quickbird are used to assess the quality of the fusion algorithm. After selecting the appropriate intrinsic mode function （IMF） for the merger on the basis of EMD analysis on specific row （column） pixel gray value series, the fusion scheme gives a fused image, which is compared with generally used fusion algorithms （wavelet, IHS, Brovey）. The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original images. To assess quality of an image after fusion, information entropy and standard deviation are applied to assess spatial details of the fused images and correlation coefficient, bias index and warping degree for measuring distortion between the original image and fused image in terms of spectral information. For the proposed fusion algorithm, better results are obtained when EMD algorithm is used to perform the fusion experience. 相似文献
2.
Classification is always the key point in the field of remote sensing. Fuzzy c-Means is a traditional clustering algorithm that has been widely used in fuzzy clustering. However, this algorithm usually has some weaknesses, such as the problems of falling into a local minimum, and it needs much time to accomplish the classification for a large number of data. In order to overcome these shortcomings and increase the classification accuracy, Gustafson-Kessel （GK） and Gath-Geva （GG） algorithms are proposed to improve the traditional FCM algorithm which adopts Euclidean distance norm in this paper. The experimental result shows that these two methods are able to detect clusters of varying shapes, sizes and densities which FCM cannot do. Moreover, they can improve the classification accuracy of remote sensing images. 相似文献
3.
ZHOU Jiaogen GUAN Jihong LI Pingxiang 《地球空间信息科学学报》2007,10(2):137-144
Spatial objects have two types of attributes: geometrical attributes and non-geometrical attributes, which belong to two different attribute domains (geometrical and non-geometrical domains). Although geometrically scattered in a geometrical domain, spatial objects may be similar to each other in a non-geometrical domain. Most existing clustering algorithms group spatial datasets into different compact regions in a geometrical domain without considering the aspect of a non-geometrical domain. However, many application scenarios require clustering results in which a cluster has not only high proximity in a geometrical domain, but also high similarity in a non-geometrical domain. This means constraints are imposed on the clustering goal from both geometrical and non-geometrical domains simultaneously. Such a clustering problem is called dual clustering. As distributed clustering applications become more and more popular, it is necessary to tackle the dual clustering problem in distributed databases. The DCAD algorithm is proposed to solve this problem. DCAD consists of two levels of clus- tering: local clustering and global clustering. First, clustering is conducted at each local site with a local clustering algorithm, and the features of local clusters are extracted. Second, local features from each site are sent to a central site where global clustering is obtained based on those features. Experiments on both artificial and real spatial datasets show that DCAD is effective and efficient. 相似文献
4.
ZHENG Zhaobao 《地球空间信息科学学报》2000,3(3):14-18
This paper introduces the principle of genetic algorithm and the basic method of solving Markov random field parameters.Focusing on the shortcomings in present methods,a new method based on genetic algorithms is proposed to solve the parameters in the Markov random field.The detailed procedure is discussed.On the basis of the parameters solved by genetic algorithms,some experim ents on classification of aerial images are given.Experimental results show that the proposed method is effective and the classification results are satisfactory. 相似文献
5.
SHI XiaoyanHU YujuLU XiangdongSHI Xiaoyan Lecturer School of Land Science WTUSM Wuhan China 《地球空间信息科学学报》1998,(1)
A geometric algorithm for Tilted-Camera Perspective（TCP）projec-tion is proposed in this paper based on the principle of perspective projection.Ac-cording to that,the difference between TCP projection and External Perspective（EXP）projection is analyzed.It is put forward prerequisites making these twoprojections were compatible,and some examples are given. 相似文献
6.
DU Qingyun WU HehaiDU Qingyu Associate Professor School of Land Science WTUSM Wuhan China 《地球空间信息科学学报》1998,(1)
The main purpose to develop a Map Graphic Workstation on thewidely used micro-computer is that by it the whole processing of map data fromcapturing,managing,editing,updating to graphic outputting can be realized.Map Digitization System（MDS）is the software system to deal with the initial andalso the most important processing.In this paper,the authors introduce a MDSon a micro-computer based Map Grphic Workstation that has been qualitified forthe producation of digital map.Since the system is designed totally independentlyand in the general frame of the Map Graphic Workstation,the capturing and man-aging and other processings for map data are in an integral manner,in which theproducation of digital map can be fulfilled conveniently.At the same time,thesystem is flexible for function extension and widely applicable to the data from dif-ferent sources and with different information characterisitcs(e.g.,the processingof Chinese characters on map). 相似文献
7.
FENGYucai YIBaolin 《地球空间信息科学学报》2004,7(4):297-302
Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries. 相似文献
8.
SHAZongyao BIANFuling 《地球空间信息科学学报》2005,8(1):57-63
This paper introduces some definitions and defines a set of calculating indexes to facilitate the research, and then presents an algorithm to complete the spatial clustering result comparison between different clustering themes. The research shows that some valuable spatial correlation patterns can be further found from the clustering result comparison with multi-themes, based on traditional spatial clustering as the first step. Those patterns can tell us what relations those themes have, and thus will help us have a deeper understanding of the studied spatial entities. An example is also given to demonstrate the principle and process of the method. 相似文献
9.
A space-filling curve in 2,3,or higher dimensions can be thought as a path of a continuously moving point.As its main goal is to preserve spatial proximity,this type of curves has been widely used in the design and implementation of spatial data structures and nearest neighbor-finding techniques.This paper is essentially focused on the efficient representation of Digital Ele-vation Models(DEM) that entirely fit into the main memory.We propose a new hierarchical quadtree-like data structure to be built over domains of unrestricted size,and a representation of a quadtree and a binary triangles tree by means of the Hilbert and the Sierpinski space-filling curves,respectively,taking into account the hierarchical nature and the clustering properties of this kind of curves.Some triangulation schemes are described for the space-filling-curves-based approaches to efficiently visualize multiresolu-tion surfaces. 相似文献
10.
FAN Hong ZHANG Jianqing ZHANG Zuxun LIU Zhifang FAN Hong Associate Professor National Laboratory for Information Engineering in Surveying Mapping Remote Sensing WTUSM Luoyu Road Wuhan China 《地球空间信息科学学报》1999,2(1):68-72
The change of house often brings on the change of DSM in an area over different periods. If we can apply information of the height of houses to reinforce the house change detection, the reliability and efficiency of detection methods will be improved greatly.From this viewpoint, a new approach taking advantage of both height data from an image pair and image data is proposed to detect the house change in urban area and is called "data fusion technology". 相似文献
11.
Spatial clustering is widely used in many fields such as WSN (Wireless Sensor Networks), web clustering, remote sensing and so on for discovery groups and to identify interesting distributions in the underlying database. By discussing the relationships between the optimal clustering and the initial seeds, a clustering validity index and the principle of seeking initial seeds were proposed, and on this principle we recommend an initial seed-seeking strategy: SSPG (Single-Shortest-Path Graph). With SSPG strategy used in clustering algorithms, we find that the result of clustering is optimized with more probability. At the end of the paper, according to the combinational theory of optimization, a method is proposed to obtain optimal reference k value of cluster number, and is proven to be efficient. 相似文献
12.
提出了初始种子选取原则及其基于这个原则的“单连通最短路径图”的初始种子选择方法,能自动发现数据集种密度相对较大的区域,并根据预先设定的聚类数目自动获寥最优的初始种子集合。实验结果证明了该方法具有较高的正确性,有效提高了空间聚类效率。 相似文献
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针对K-均值聚类存在的初始聚类中心不稳定、聚类数目难以确定的问题,提出利用正交投影散度(OPD)优化K-均值算法的初始聚类中心,设计了RD指标函数用于估计聚类数目k。将所提出的算法应用于高光谱影像特征提取与端元提取分析,实验结果表明,所提出算法的性能高于已有的类似算法。 相似文献
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空间聚类是挖掘空间知识的重要手段之一。针对现有方法难以处理几何、分布特征差异大的面群聚类问题,本文提出了一种面要素分布密度的描述参数—聚集度,并设计了一种自然面群聚类方法。首先,分析了面要素分布密度的影响因子,定义了聚集度的概念,设计其计算方法并验证其有效性及优势;然后,基于聚集度和边界最短距离建立相邻面从属关系,识别聚类中心,完成初始群组的构建;最后,围绕群组特征设计了边缘检测和群组合并模型,实现了邻近相似群组的合并。试验表明,相较于最小生成树、强度函数聚类方法,本文方法兼顾几何特征、分布特征的复杂性,有效提升了自然面群的聚类效果。 相似文献
17.
遥感影像模糊聚类方法可以在无需样本分布信息的情况下获取比硬聚类方法更高的分类精度,但其仍依赖先验知识来确定影像地物的类别数。本文提出了一种基于自适应差分进化的遥感影像自动模糊聚类方法,该方法利用差分进化搜索速度快、计算简单、稳定性高的优点,以Xie-Beni指数为优化的适应度函数,在无需先验类别信息的情况下自动判定图像的类别数,并结合局部搜索算子对遥感影像进行最优化聚类。通过模拟影像以及两幅真实遥感图像的分类实验表明,本文方法不仅可以正确地自动获取地物类别数,而且能够获得比K均值、ISODATA以及模糊K均值方法更高的分类精度。 相似文献
18.
模糊C均值聚类是一种经典的非监督聚类模型,成功地应用于遥感影像分类。但是该方法对初始值敏感,容易陷入局部最优解;同时聚类时仅考虑光谱信息,忽略了空间信息。本文提出了一种新的基于马尔科夫随机场的模糊C均值聚类方法,该方法把马尔科夫随机场和模糊C均值结合在一起。初始值依据第一主成分的密度函数确定,这样克服了对初始值的依赖性,又在聚类的时候考虑了空间信息。通过实例数据验证,所提出的方法分类精度优于传统的模糊C均值模型。 相似文献
19.
基于自组织神经网络的空间点群聚类及其应用分析 总被引：2，自引：0，他引：2
探讨了采用自组织神经网络进行离散空间点群聚类的原理、方法及应用分析,提出了一种兼顾几何距离和属性特征的广义Euclid距离,并将其作为聚类统计量.并以实例验证了采用自组织空间聚类进行空间点群的数据分类、异常数据检验、均质区域划分等是有效的. 相似文献
20.
针对传统上单独采用K-means或DBSCAN等方法对共享单车位置数据聚类时造成的聚类结果与真实的聚类结构不符的问题,本文提出了一种基于共享单车时空大数据的细粒度聚类方法(FGCM)。该方法通过DBSCAN进行初始聚类,并在此基础上采用GMM-EM算法进行细部聚类,以提取细粒度层级的热点区域。试验表明,该方法可根据密度阈值排除噪声和离群值,无需指定细部聚类簇数,簇的形状和大小比较灵活。在对共享单车大数据位置特征进行聚类时,与传统的单独采用K-means或DBSCAN的方法相比,FGCM具备更高的精细程度,能够充分展现共享单车的实际聚集特征,可用于规划共享单车电子围栏等设施,在不降低通勤效率的基础上规范共享单车的停放问题。 相似文献