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A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis 总被引:2,自引:0,他引:2
Yu Liu Qinghua Guo Maggi Kelly 《ISPRS Journal of Photogrammetry and Remote Sensing》2008,63(4):461-475
Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent “line-like objects” and “point-like objects” are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis. 相似文献
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柯金朴 《测绘与空间地理信息》2008,31(3)
地下管线是城市生存发展的命脉,准确掌握地下各种管线的状况,是搞好城市建设和规划管理工作的基础。本文根据石狮市城市规划建设现状,探讨地下管线普查和采集的方法,提出建立地下管线信息系统等有关问题。 相似文献
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在平顶山矿工路路面改造工程中,使用GX-2型及RD-4000型地下管线探测仪探测地下管网布设情况。根据地下管线种类、管线布设方位、埋置深度、探测难度大小进行了多次试验,在此基础上确定了电磁探测技术与方法:利用直连法提高被测管线中的交变电流,压制邻近平行管线和地下介质中的异常反映;在多管并存、且间距较小的情况下,应选择“梯度法”对磁场水平分量垂直梯度ΔHx进行观测,以得到最大清晰异常;另外,还应根据具体情况,合理选择诸如压制旁侧管线法、选择发射法、偏移感应法、动源发射法等发射方式,保证目标管线中有较强异常呈现。在管线密集区,应尽可能地降低工作频率,以减小旁侧管线中产生的二次电流及二次磁场;为防止信噪比下降,可适当减小收发距,以提高接收机的灵敏度。 相似文献
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Xian-Huan Wen 《Mathematical Geology》1994,26(6):717-731
Field tests of hydraulic conductivity (e.g., injection test, pumping test, etc.) in low permeability formations are subject to censoring due to the detection limit of the instruments used. An iterative method of estimating the mean and variance of hydraulic conductivity data with a presumed log-normal distribution function is presented. This method accounts for the data that are actually below the lower detection limit (called truncated data) and thus gives distribution parameters that are more representative for the underlying distribution. The proposed method is then tested on two simulated normally distributed random datasets having different variances. The results show that the means and variances estimated by the proposed method are very accurate. Finally, the method is used to estimate the mean and variance of hydraulic conductivity data from single hole water injection tests in a fractured geological formation. 相似文献
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Chang-Jo F. Chung 《Mathematical Geology》1993,25(7):851-865
Multivariate statistical analyses have been extensively applied to geochemical measurements to analyze and aid interpretation of the data. Estimation of the covariance matrix of multivariate observations is the first task in multivariate analysis. However, geochemical data for the rare elements, especially Ag, Au, and platinum-group elements, usually contain observations the below detection limits. In particular, Instrumental Neutron Activation Analysis (INAA) for the rare elements produces multilevel and possibly extremely high detection limits depending on the sample weight. Traditionally, in applying multivariate analysis to such incomplete data, the observations below detection limits are first substituted, for example, each observation below the detection limit is replaced by a certain percentage of that limit, and then the standard statistical computer packages or techniques are used to obtain the analysis of the data. If a number of samples with observations below detection limits is small, or the detection limits are relatively near zero, the results may be reasonable and most geological interpretations or conclusions are probably valid. In this paper, a new method is proposed to estimate the covariance matrix from a dataset containing observations below multilevel detection limits by using the marginal maximum likelihood estimation (MMLE) method. For each pair of variables, sayY andZ whose observations containing below detection limits, the proposed method consists of three steps: (i) for each variable separately obtaining the marginal MLE for the means and the variances,
,
,
, and
forY andZ: (ii) defining new variables by
and
and lettingA=C+D andB=C–D, and obtaining MLE for variances,
and
forA andB; (iii) estimating the correlation coefficient YZ by
and the covariance
YZ
by
. The procedure is illustrated by using a precious metal geochemical data set from the Fox River Sill, Manitoba, Canada. 相似文献