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无人机遥感影像中农村房屋信息快速提取 总被引：2，自引：0，他引：2
《国土资源遥感》2016,(3)
针对无人机遥感技术应用中信息提取自动化、智能化不足的问题,提出了一种基于面向对象分割的农村房屋信息提取方法。该方法首先利用双边滤波器滤掉影像中的噪声,然后利用移动均值算法分割影像,最后根据分割后房屋对象的特征建立提取规则,对房屋信息进行提取。实验结果表明,该方法可有效提取无人机遥感影像中的农村房屋信息,平均提取精度约为92%。 相似文献
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提出了一种以震后单一时相高空间分辨率光学遥感影像为基础,融合纹理特征和形态特征的地震倒塌房屋自动提取方法,研究了不同尺度纹理特征和形态特征在倒塌房屋提取中的作用和表现。以5.12汶川地震作为研究实例,结果表明,本方法能够有效提取地震倒塌房屋。倒塌房屋产品精度和用户精度分别为86.65%和86.35%,Kappa系数为0.790 6。 相似文献
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在充分利用房屋影像特征和目标领域知识的基础上,构造了基于方向信息的弱边缘检测、大跨度直线桥线段提取、角点分析与检测、房屋轮廓推理与证实、房屋轮廓修整与表达等关键算法,以控制注意力焦点处理机制和影像级、符号级结合的运算方式,对大比例尺航空影像中的房屋目标进行提取。本文详细地描述了此方法,并给出了在提取被树荫等环境因素干扰的规整平顶、坡顶房屋方面所取得的效果。 相似文献
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通过分析遥感影像中直角型房屋特点,本文提出一种新的房屋提取方法:利用Freeman编码推导出常见直角型房屋代码,使得每一种形状房屋都具有惟一编号,且编号不随房屋大小、方位及位置改变而改变,利用Hough变换提取房屋角点并剔除伪角点,最后利用模式匹配方法获得各个角点之间的连接关系。实验结果表明该方法具有较强的抗噪性,能有效提取影像中直角型房屋。 相似文献
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一种具有抗弱边缘能力的航空影像房屋自动提取方法 总被引：1，自引：0，他引：1
在充分利用房屋影像特征和目标领域知识的基础上，构造了基于方向信息的弱边缘检测、大跨度直线桥线段提取、角点分析与检测、房屋轮廓推理与证实、房屋轮廓修整与表达等关键算法，以控制注意力焦点处理机制和影像级、符号级结合的运算方式，对大比例尺航空影像中的房屋目标进行提取。本详细地描述了此方法，并给出了在提取被树荫等环境因素干扰的规整平顶、坡顶房屋方面所取得的效果。 相似文献
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针对传统遥感影像质量评价中云层覆盖量无法定量评价的问题,文章提出采用利用边缘信息的阈值分割结合数学形态学方法来提取遥感影像云层覆盖范围。利用边缘信息的阈值分割方法能够有效利用影像自身信息来改善分割结果,再结合形态学方法,进而能消除道路、房屋等大部分噪声信息,最终实现遥感影像上不同特征云层覆盖范围的自动提取。基于浙江全省高分辨率遥感影像的实验结果表明:该方法能够快速有效地识别出遥感影像上云层覆盖范围,研究结果对于遥感影像云层覆盖的自动评价具有参考价值。 相似文献
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几何约束与影像分割相结合的快速半自动房屋提取 总被引：1，自引：0，他引：1
通过充分利用影像中的几何信息 ,针对航空影像中常见的平顶直角型和人字型房屋 ,提出了一种几何约束与影像分割相结合的快速半自动房屋提取方法。实验结果证明 ,该方法方便快捷、行之有效 相似文献
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RS与GIS一体化数据结构的研究 总被引：1，自引：0，他引：1
详细阐述了RS与GIS一体化的概念 ,通过对RS与GIS一体化方面的研究与分析 ,进一步明确RS与GIS一体化对空间数据存储结构的要求 ,着重探讨了几种典型的用于RS与GIS一体化的数据结构 ,针对现有数据结构存在的问题与不足 ,提出了一种具有普遍适用价值的基于语义网络的空间数据存储结构 ,并给出一个应用实例 相似文献
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The integration of remote sensing (RS) with geographical information system (GIS) is a hotspot in geographical information science. A good database structure is important to the integration of RS with GIS, which should be beneficial to the complete integration of RS with GIS, able to deal with the disagreement between the resolution of remote sensing images and the precision of GIS data, and also helpful to the knowledge discovery and exploitation. In this paper, the database structure storing the spatial data based on semantic network is presented. This database structure has several advantages. Firstly, the spatial data is stored as raster data with space index, so the image processing can be done directly on the GIS data that is stored hierarchically according to the distinguishing precision. Secondly, the simple objects are aggregated into complex ones. Thirdly, because we use the indexing tree to depict the relationship of aggregation and the indexing pictures expressed by 2-D strings to describe the topology structure of the objects, the concepts of surrounding and region are expressed clearly and the semantic content of the landscape can be illustrated well. All the factors that affect the recognition of the objects are depicted in the factor space, which provides a uniform mathematical frame for the fusion of the semantic and non-semantic information. Lastly, the object node, knowledge node and the indexing node are integrated into one node. This feature enhances the ability of system in knowledge expressing, intelligent inference and association. The application shows that this database structure can benefit the interpretation of remote sensing image with the information of GIS. 相似文献
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物体空间关系指的是物体在欧氏空间中的邻近关系,根据图像中包含物体的邻近关系解决图像匹配的问题。本文首先基于对比机制训练物体块特征提取网络,构建物体块深度特征,该特征可以有效匹配不同图像中的相同物体块;其次,基于已有的先验图像数据推理表达图像中物体的空间邻近关系,构建场景物体空间邻近图;进而基于该空间邻近图计算场景图像对的空间邻近度,完成图像空间关系匹配。试验表明不匹配图像间的空间邻近度一般为0,而匹配图像间的空间邻近度一般大于0,本文空间关系匹配涉及多个物体间的相互关系,具有更强的稳健性,其匹配效果明显优于对比试验中的其他方法,可以高效稳定地完成图像匹配任务。 相似文献
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YU Nenghai WANG Xiaogang LIU Zhengkai ZHANG Rong 《地球空间信息科学学报》2001,4(3):21-28
1 ＴｈｅｃｏｎｃｅｐｔｏｆｔｈｅｉｎｔｅｇｒａｔｉｏｎｏｆＲＳｗｉｔｈＧＩＳＴｈｅｉｎｔｅｇｒａｔｉｏｎｏｆｒｅｍｏｔｅｓｅｎｓｉｎｇ (ＲＳ)ｗｉｔｈｇｅｏ ｇｒａｐｈｉｃａｌｉｎｆｏｒｍａｔｉｏｎｓｙｓｔｅｍ (ＧＩＳ)ｉｓａｈｏｔｓｐｏｔｉｎｇｅｏｇｒａｐｈｉｃａｌｉｎｆｏｒｍａｔｉｏｎｓｃｉｅｎｃｅ .ＴｈｅｃｏｎｃｅｐｔｏｆｔｈｅｉｎｔｅｇｒａｔｉｏｎｏｆＲＳｗｉｔｈＧＩＳ ,ｉｎｔｈｅｖｉｅｗｏｆＰｒｏｆ.ＬｉＤｅｒｅｎ ,ｉｓｔｈａｔＲＳｉｓｔｈｅｗａｙｔｏｏｂｔａｉｎｔｈｅｉｎｆｏｒｍａ ｔｉ… 相似文献
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结合对象关系特征的高分辨率卫星影像建筑物识别方法 总被引：1，自引：0，他引：1
基于面向对象特征影像分析的思想,提出了一种结合建筑物和阴影对象邻近关系特征的建筑物识别提取方法。在多尺度影像
分割的基础上,利用对象的光谱和形状等特征,建立简单的分类决策树,提取粗略的建筑物候选区和相对准确的阴影区。计算相邻
近阴影对象和建筑物对象的关系特征,建立简单的知识规则,即可从建筑物候选区中消除广场等噪音,获得准确有效的建筑物目标
信息。通过QuickBird卫星影像的实验,证明了该方法在高分辨率卫星影像建筑物目标识别中具有相当的适用性和准确性。 相似文献
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The composition and arrangement of spatial entities, i.e., land cover objects, play a key role in distinguishing land use types from very high resolution (VHR) remote sensing images, in particular in urban environments. This paper presents a new method to characterize the spatial arrangement for urban land use extraction using VHR images. We derive an adjacency unit matrix to represent the spatial arrangement of land cover objects obtained from a VHR image, and use a graph convolutional network to quantify the spatial arrangement by extracting hidden features from adjacency unit matrices. The distribution of the spatial arrangement variables, i.e., hidden features, and the spatial composition variables, i.e., widely used land use indicators, are then estimated. We use a Bayesian method to integrate the variables of spatial arrangement and composition for urban land use extraction. Experiments were conducted using three VHR images acquired in two urban areas: a Pleiades image in Wuhan in 2013, a Superview image in Wuhan in 2019, and a GeoEye image in Oklahoma City in 2012. Our results show that the proposed method provides an effective means to characterize the spatial arrangement of land cover objects, and produces urban land use extractions with overall accuracies (i.e., 86% and 93%) higher than existing methods (i.e., 83% and 88%) that use spatial arrangement information based on building types on the Pleiades and GeoEye datasets. Moreover, it is unnecessary to further categorize the dominant land cover type into finer types for the characterization of spatial arrangement. We conclude that the proposed method has a high potential for the characterization of urban structure using different VHR images, and for the extraction of urban land use in different urban areas. 相似文献
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《ISPRS Journal of Photogrammetry and Remote Sensing》1999,54(4):263-272
In this paper, we address the problem of content-based image retrieval using queries on shape and topology. We focus on the particularities of image databases encountered in typical topographic applications and present the development of a spatial data management system that enables such queries. The query requires user-provided sketches of the shape and spatial configuration of the object (or objects) which should appear in the images to be retrieved. The objective of the search is to retrieve images that contain a configuration of objects sufficiently similar to the one specified in the query. Our approach combines the design of an integrated database with the development of a feature library and the necessary matching tools. In this paper, we present our overall scheme, introduce some individual database components, and provide some implementation results. 相似文献
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We present an automatic approach for object extraction from very high spatial resolution (VHSR) satellite images based on Object-Based Image Analysis (OBIA). The proposed solution requires no input data other than the studied image. Not input parameters are required. First, an automatic non-parametric cooperative segmentation technique is applied to create object primitives. A fuzzy rule base is developed based on the human knowledge used for image interpretation. The rules integrate spectral, textural, geometric and contextual object proprieties. The classes of interest are: tree, lawn, bare soil and water for natural classes; building, road, parking lot for man made classes. The fuzzy logic is integrated in our approach in order to manage the complexity of the studied subject, to reason with imprecise knowledge and to give information on the precision and certainty of the extracted objects. The proposed approach was applied to extracts of Ikonos images of Sherbrooke city (Canada). An overall total extraction accuracy of 80% was observed. The correctness rates obtained for building, road and parking lot classes are of 81%, 75% and 60%, respectively. 相似文献
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面向对象分类提取高分辨率多光谱影像建筑物 总被引：1，自引：0，他引：1
初步测试利用基于知识规则的面向对象分类方法从高分辨率Ikonos卫星影像上提取建筑物,包括:融合1 m全色和4 m多光谱波段影像,生成1 m分辨率的多光谱融合影像;分割融合影像;利用影像对象的光谱和空间特征执行基于对象的分类。面向对象分类提取结果与传统的基于像元最大似然分类结果进行对比,表明面向对象分类方法更适用于提取高分辨率遥感影像中的建筑物。 相似文献