Automatic registration of aerophotos based on SUSAN operator     

张迁 《测绘科学》2006,(Z1)

The technique of image matching is the basis of image fusion,image mosaic and scene 3D reconstruction.In the paper a novel image registration method based on SUSAN operator is proposed.Firstly,Corner points are extracted by using SUSAN(Smallest Univalue Segment Assimilating Nucleus) operator.Then matched corner points are selected through coarse matching and fine matching.Based on such corner pairs,aerophotos are registered automatically.  相似文献   

基于地理要素编码的数字地形图入库方法实现及应用   总被引：1，自引：0，他引：1  

刘德儿  肖海平 《国土资源信息化》2009,(1):37-40

目前建设城市基础地理信息系统的主要数据来源是各城市已经采集的不同比例尺的数字化地形图,而数字化地形图不能直接被GIS软件操作。本研究从实际出发,提出基于地理要素编码的数字地形图入库设计方法,将ArcGIS Engine和Objects Arx2007相结合进行嵌入式二次开发,利用C#,在.NET2005平台下得以实现,并在某城市的基础地理信息系统建设中得到实际应用。  相似文献   

An automated approach to vertical road characterisation using mobile LiDAR systems: Longitudinal profiles and cross-sections     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

The characterisation the vertical profiles and cross-sections of roads is important for the verification of proper construction and road safety assessment. The goal of this paper is the extraction of geometric parameters through the automatic processing of mobile LiDAR system (MLS) point clouds. Massive and complex datasets provided by the MLS are processed using a hierarchical strategy that includes segmentation, principal component analysis (PCA)-based orthogonal regression, filtering and parameter extraction procedures. Best-fit geometric parameters act as a vertical road model for both linear parameters (slope and vertical curves) and cross-sections (superelevations). The proposed automatic processing approach gives satisfactory results for the analysed scenario.  相似文献   

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

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A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

In recent years, it has been widely agreed that spatial features derived from textural, structural, and object-based methods are important information sources to complement spectral properties for accurate urban classification of high-resolution imagery. However, the spatial features always refer to a series of parameters, such as scales, directions, and statistical measures, leading to high-dimensional feature space. The high-dimensional space is almost impractical to deal with considering the huge storage and computational cost while processing high-resolution images. To this aim, we propose a novel multi-index learning (MIL) method, where a set of low-dimensional information indices is used to represent the complex geospatial scenes in high-resolution images. Specifically, two categories of indices are proposed in the study: (1) Primitive indices (PI): High-resolution urban scenes are represented using a group of primitives (e.g., building/shadow/vegetation) that are calculated automatically and rapidly; (2) Variation indices (VI): A couple of spectral and spatial variation indices are proposed based on the 3D wavelet transformation in order to describe the local variation in the joint spectral-spatial domains. In this way, urban landscapes can be decomposed into a set of low-dimensional and semantic indices replacing the high-dimensional but low-level features (e.g., textures). The information indices are then learned via the multi-kernel support vector machines. The proposed MIL method is evaluated using various high-resolution images including GeoEye-1, QuickBird, WorldView-2, and ZY-3, as well as an elaborate comparison to the state-of-the-art image classification algorithms such as object-based analysis, and spectral-spatial approaches based on textural and morphological features. It is revealed that the MIL method is able to achieve promising results with a low-dimensional feature space, and, provide a practical strategy for processing large-scale high-resolution images.  相似文献   

Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used.  相似文献   

Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

Many municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for objective methods and quantitative metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the development and testing of a new approach for using technical mapping standards in the quality assessment of buildings automatically extracted from VHR satellite imagery. Feature extraction software was employed to map buildings present in a pansharpened QuickBird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference data set, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10,000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality assessed based on planimetric deviation from the reference map. Tests were developed and metrics analyzed considering thresholds and standards for the large mapping scales most frequently used by municipalities. Results show that values for completeness varied with mapping scales and were only slightly superior for scale 1:10,000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10,000, while no buildings were compliant with the specification for scale 1:1000.  相似文献   

Assessing integration of intensity,polarimetric scattering,interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

Synthetic aperture radar (SAR) is an important alternative to optical remote sensing due to its ability to acquire data regardless of weather conditions and day/night cycle. The Phased Array type L-band SAR (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) provided new opportunities for vegetation and land cover mapping. Most previous studies employing PALSAR investigated the use of one or two feature types (e.g. intensity, coherence); however, little effort has been devoted to assessing the simultaneous integration of multiple types of features. In this study, we bridged this gap by evaluating the potential of using numerous metrics expressing four feature types: intensity, polarimetric scattering, interferometric coherence and spatial texture. Our case study was conducted in Central New York State, USA using multitemporal PALSAR imagery from 2010. The land cover classification implemented an ensemble learning algorithm, namely random forest. Accuracies of each classified map produced from different combinations of features were assessed on a pixel-by-pixel basis using validation data obtained from a stratified random sample. Among the different combinations of feature types evaluated, intensity was the most indispensable because intensity was included in all of the highest accuracy scenarios. However, relative to using only intensity metrics, combining all four feature types increased overall accuracy by 7%. Producer’s and user’s accuracies of the four vegetation classes improved considerably for the best performing combination of features when compared to classifications using only a single feature type.  相似文献   

宾川小龙潭斑岩铜钼矿矿化特征及控矿条件     

张金学  罗洪昌  刘利超  杨枝斌  田锐锋 《云南地质》2014,(2):214-218

区域性的程海深大断裂是该区的导岩、导矿构造,直接控制了富碱性斑岩和次级构造的展布,富碱性斑岩又是区内铜钼矿化的直接成矿因素,所以应重视沿北东向构造—岩浆带的找矿工作.  相似文献   

香格里拉县松诺斑岩体与普朗斑岩体特征对比     

王建华  ;李文昌 《云南地质》2014,(2):185-187

松诺斑岩体位于云南省香格里拉县境内,其与南部的普朗超大型斑岩铜矿距离十分靠近.随着近年来普朗铜矿外围找矿工作的展开,松诺地区显示出良好的找矿前景.本文重点就松诺斑岩体的地球化学特征,与普朗斑岩体的地球化学特征进行了对比讨论,以揭示它们之间的同源关系.  相似文献