共查询到20条相似文献，搜索用时 125 毫秒
1.
复杂城区边界通常存在建筑物大小差异较大、周边林区高低起伏、散点建筑成片出现的情况，对城区边界提取算法造成严重干扰。针对这一问题，本文提出一种基于拓扑插值和光谱特征的高分辨率遥感影像复杂城区边界提取方法。一方面，通过对大型建筑特征点进行拓扑插值，避免由于大型建筑特征点稀疏造成的城区边界缺失；另一方面，利用植被光谱特征来滤除城区周边高低起伏的林区和散点建筑带来的冗余特征点，从而有效抑制城区误提取。通过试验和对比分析表明，本文方法在提取复杂城区边界方面，具有较好的稳健性和较高的精度。 相似文献
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Soe Win Myint 《国际地球制图》2013,28(4):29-40
Abstract Attempts to analyze urban features and to classify land use and land cover directly from high‐resolution satellite data with traditional computer classification techniques have proven to be inefficient for two primary reasons. First, urban landscapes are composed of complex features. Second, traditional classifiers employ spectral information based on single pixel value and ignore a great amount of spatial information. Texture plays an important role in image segmentation and object recognition, as well as in interpretation of images in a variety of applications. This study analyzes urban texture features in multi‐spectral image data. Recent developments in the very powerful mathematical theory of wavelet transforms have received overwhelming attention by image analysts. An evaluation of the ability of wavelet transform in urban feature extraction and classification was performed in this study, with six types of urban land cover features classified. The preliminary results of this research indicate that the accuracy of texture analysis in classifying urban features in fine resolution image data could be significantly improved with the use of wavelet transform approach. 相似文献
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An Evaluation of Four Different Wavelet Decomposition Procedures for Spatial Feature Discrimination in Urban Areas 总被引：2，自引：0，他引：2
Texture or spatial arrangement of neighborhood objects and features plays an important role in the human visual system for pattern recognition and image classification. The traditional spectral–based image processing techniques have proven inadequate for urban land use and land cover mapping from images acquired by the current generation of fine–resolution satellites. This is because of the high frequency spatial arrangements or complex nature of urban features. There is a need for an effective algorithm to digitally classify urban land use and land cover categories using high–resolution image data. Recent studies using wavelet transforms for texture analysis have generally reported better accuracy. Based on a high–resolution ATLAS image, this study illustrates four different wavelet decomposition procedures – the standard, horizontal, vertical, and diagonal decompositions – for urban land use and land cover feature extraction with the use of 33×33 pixel samples. The standard decomposition approach was found to be the most efficient approach in urban texture analysis and classification. For comparison purposes and to better evaluate the accuracy of wavelet approaches in image classification, spatial autocorrelation techniques (Moran's I and Geary's C ) and the spatial co–occurrence matrix method were also examined. The results suggest that the wavelet transform approach is superior to all other approaches. 相似文献
4.
光谱和形状特征相结合的高分辨率遥感图像的建筑物提取方法 总被引：3，自引：0，他引：3
针对高分辨率遥感影像具有较为丰富的地物属性"谱相"信息和空间分布及其组合"图式"信息的特点,提出了一种光谱和形状特征相结合的建筑物自动提取方法。在多尺度分割和矢量化基础上,根据建筑物的形状、光谱特征,从特征基元中自动选取样本,并计算其特征;通过根据建筑物形状、光谱、纹理构造的模板,在整景影像上进行建筑区域识别,并在建筑区域内提取建筑物外部轮廓。实验表明,本算法具有较高的识别率和较低的误识别率。 相似文献
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国产高分卫星分辨率的不断提高,使其可以从几何形态、纹理结构及光谱信息等不同侧面实现对城市地表要素的精细描述。与面向对象分类技术相比,深度学习技术的快速发展,使得城市建筑物提取的精度不断提高。然而,由于道路两旁高大建筑物及树木的遮挡,城市道路的提取精度依然有限。本文在利用卷积神经网络提取建筑物的基础上,利用OSM面状道路数据及城市边界数据,结合植被指数和水体指数,借助空间图层叠加,使得城市建筑物、道路、植被和水体提取总体精度优于90%,为国产高分影像辅助城市精细化管理和应用提供了有效解决方案。 相似文献
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TerraSAR-X satellite acquires very high spatial resolution data with potential for detailed land cover mapping. A known problem with synthetic aperture radar (SAR) data is the lack of spectral information. Fusion of SAR and multispectral data provides opportunities for better image interpretation and information extraction. The aim of this study was to investigate the fusion between TerraSAR-X and Landsat ETM+ for protected area mapping using high pass filtering (HPF), principal component analysis with band substitution (PCA) and principal component with wavelet transform (WPCA). A total of thirteen land cover classes were identified for classification using a non-parametric C 4.5 decision tree classifier. Overall classification accuracies of 74.99%, 83.12% and 85.38% and kappa indices of 0.7220, 0.8100 and 0.8369 were obtained for HPF, PCA and WPCA fusion approaches respectively. These results indicate a high potential for a combined use of TerraSAR-X and Landsat ETM+ data for protected area mapping in Uganda. 相似文献
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《Geoscience and Remote Sensing Letters, IEEE》2008,5(4):653-657
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With the availability of very high resolution multispectral imagery, it is possible to identify small features in urban environment. Because of the multiscale feature and diverse composition of land cover types found within the urban environment, the production of accurate urban land cover maps from high resolution satellite imagery is a difficult task. This paper demonstrates the potential of 8 bands capability of World View 2 satellite for better automated feature extraction and discrimination studies. Multiresolution segmentation and object based classification techniques were then applied for discrimination of urban and vegetation features in a part of Dehradun, Uttarakhand, India. The study demonstrates that scale, colour, shape, compactness and smoothness have a significant influence on the quality of image objects achieved, which in turn governs the classified result. The object oriented analysis is a valid approach for analyzing high spatial and spectral resolution images. World View 2 imagery with its rich spatial and spectral information content has very high potential for discrimination of the less varied varieties of vegetation. 相似文献
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Classification approaches for urban areas are mostly of qualitative and semantic nature. They produce interpreted classes similar to those from land cover and land use classifications. As a complement to those classes, quantitative measures directly derived from the image could lead to a metric characterization of the urban area. While these metrics lack of qualitative interpretation they are able to provide objective measure of the urban structures.Such quantitative measures are especially important in rapidly growing cities since, beside of the growth in area, they can provide structural information for specific areas and detect changes. Rustenburg, which serves as test area for the present study, is amongst the fastest growing cities in South Africa. It reveals a heterogeneous face of housing and building structures reflecting social and/or economic differences often linked to the spatial distribution of industrial and local mining sites. Up to date coverage with aerial photographs is provided by aerial surveys in regular intervals. Also recent satellite systems provide imagery with suitable resolution. Using such set of very high resolution images a fully automated algorithm has been developed which outputs metric classes by systematically combining important measures of building structure. The measurements are gained by decomposition of buildings directly from the imagery and by using methods from mathematical morphology. The decomposed building objects serve as basis for the computation of grid statistics. Finally a systematic combination of the single features leads to combined metrical classes.For the dominant urban structures verification results indicate an overall accuracy of at least 80% on the single feature level and 70% for the combined classes. 相似文献
10.
根据高分辨率遥感影像中城镇道路的特点,提出了一种基于特征点的道路信息提取方法。首先,对影像进行增强处理并选取感兴趣的子区域,利用改进的分水岭分割理论和阈值选择算法,结合八邻域检测方法得到道路的特征点;然后,利用回归分析方法在一定的坐标系统下得到每条道路的回归方程,根据端点坐标信息得到道路信息图;最后,利用数学形态学算法获取道路骨架图。结果表明,本方法能够精确有效地提取高分辨率遥感影像的城镇道路信息。 相似文献
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Uwe Soergel Eckart Michaelsen Antje Thiele Erich Cadario Ulrich Thoennessen 《ISPRS Journal of Photogrammetry and Remote Sensing》2009,64(5):490-500
SAR stereo image analysis for 3D information extraction is mostly carried out based on imagery taken under same-side or opposite-side viewing conditions. For urban scenes in practice stereo is up to now usually restricted to the first configuration, because increasing image dissimilarity connected with rising illumination direction differences leads to a lack of suitable features for matching, especially in the case of low or medium resolution data. However, due to two developments SAR stereo from arbitrary viewing conditions becomes an interesting option for urban information extraction. The first one is the availability of airborne sensor systems, which are capable of more flexible data acquisition in comparison to satellite sensors. This flexibility enables multi-aspect analysis of objects in built-up areas for various kinds of purpose, such as building recognition, road network extraction, or traffic monitoring. The second development is the significant improvement of the geometric resolution providing a high level of detail especially of roof features, which can be observed from a wide span of viewpoints. In this paper, high-resolution SAR images of an urban scene are analyzed in order to infer buildings and their height from the different layover effects in views taken from orthogonal aspect angles. High level object matching is proposed that relies on symbolic data, representing suitable features of urban objects. Here, a knowledge-based approach is applied, which is realized by a production system that codes a set of suitable principles of perceptual grouping in its production rules. The images are analyzed separately for the presence of certain object groups and their characteristics frequently appearing on buildings, such as salient rows of point targets, rectangular structures or symmetries. The stereo analysis is then accomplished by means of productions that combine and match these 2D image objects and infer their height by 3D clustering. The approach is tested using real SAR data of an urban scene. 相似文献
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高分辨率遥感影像建筑物分级提取 总被引：1，自引：1，他引：0
高分辨率遥感影像建筑物信息自动提取是遥感应用研究中的一个热点问题,但由于受到成像条件不同、背景地物复杂、建筑物类型多样等多个因素的影响使得建筑物的自动提取仍然十分困难。为此,在综合考虑影像光谱、几何与上下文特征的基础上,提出了一种基于面向对象与形态学相结合的高分辨率遥感影像建筑物信息分级提取方法。该方法首先利用影像的多尺度及多方向Gabor小波变换结果提取建筑物特征点;然后采用面向对象的思想构建空间投票矩阵来度量每一个像素点属于建筑物区域的概率,从而提取出建筑物区域边界;最后在提取的建筑物区域内应用形态学建筑物指数实现建筑物信息的自动提取。实验结果表明,本文方法能够高效、高精度地完成复杂场景下的建筑物信息提取,且提取结果的正确性和完整性都优于效果较好的PanTex算法。 相似文献
14.
城市建筑物信息的自动提取是城市遥感的关键技术之一,由于阴影、下垫面等多因素干扰,建筑物信息提取精度往往不稳定。本文以Pleiades卫星影像为数据源,通过改进Relief F特征筛选方法,探讨建筑物信息提取精度提高的可行性。首先构建高分辨率遥感影像建筑物基础特征空间,然后利用改进型Relief F算法分析特征对象的权重并筛选出最优特征,最后用监督分类、无特征筛选分类和基于改进型Relief F特征筛选等3种方法分别提取研究区建筑物信息,并结合实地调查数据进行精度验证。结果表明,基于改进型Relief F特征筛选的分类方法提取精度能够达到91.34%,较其他两种方法提取精度分别提高了34.31%和5.62%,且运算速度快,自动识别效率高。 相似文献
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Automatic road extraction using high resolution satellite image based on texture progressive analysis and normalized cut method 总被引：1，自引：0，他引：1
J. Senthilnath M. Rajeshwari S. N. Omkar 《Journal of the Indian Society of Remote Sensing》2009,37(3):351-361
In this paper the approach for automatic road extraction for an urban region using structural, spectral and geometric characteristics
of roads has been presented. Roads have been extracted based on two levels: Pre-processing and road extraction methods. Initially,
the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, parking
lots, vegetation regions and other open spaces). The road segments are then extracted using Texture Progressive Analysis (TPA)
and Normalized cut algorithm. The TPA technique uses binary segmentation based on three levels of texture statistical evaluation
to extract road segments where as, Normalized cut method for road extraction is a graph based method that generates optimal
partition of road segments. The performance evaluation (quality measures) for road extraction using TPA and normalized cut
method is compared. Thus the experimental result show that normalized cut method is efficient in extracting road segments
in urban region from high resolution satellite image. 相似文献
16.
基于特征的遥感图像信息融合模式研究 总被引：5，自引：4，他引：1
基于图像特征的遥感图像信息融合是在突出目标地物的空间结构和纹理特征情况下的信息融合。本文在数字图像小波多分辨率分析理论基础上,采用小波变换方法对高分辨率遥感图像的目标地物边缘进行信息增强,然后与多光谱遥感图像进行特征信息融合。在融合过程中,首先对多光谱图像中的R、G、B三个波段的图像进行小波分解,得到相应的低频图像,并对特征增强后的高分辨率图像进行小波分解,再将分解后的高频图像分别与低频图像进行融合,最后经RGB合成为彩色图像。该方法既改善了图像的清晰度和分辨率,同时也保留了原图像的光谱信息。本文最后通过融合实验验证了上述结论。 相似文献
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高空间分辨率光学遥感影像中建筑物的提取对城市空间数据库的更新、城市动态监测以及建设"智慧城市"等方面具有极其重要的意义。本文首先介绍了高空间分辨率遥感影像中建筑物的特点,然后介绍了基于高空间分辨率遥感影像中建筑物自动提取的四种主要方法,即多尺度分割提取方法;基于边缘和角点检测与匹配的提取方法;基于区域分割的提取方法和基于数学工具;新理论以及多种方法结合的提取方法,分析讨论了各种方法的研究进展以及各方法的优缺点,同时对建筑物提取研究中需要解决的问题和研究趋势进行了总结。最后对高空间分辨率遥感影像建筑物提取研究前景进行了展望,认为可以从多源或多时相数据、边缘检测以及阴影辅助作用等方面提取建筑物,提高建筑物提取精度和高分遥感影像的利用率。 相似文献
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K. N. Prudhvi Raju Sarvajeet Kumar Kshitij Mohan Manish Kumar Pandey 《Journal of the Indian Society of Remote Sensing》2008,36(3):283-288
With growing urban expanses, one of the pre-requisites for effective governance is Urban Information Systems (UIS) with content
down to individual properties (and individuals). The basic input i.e., a map, in UIS should show individual property boundaries
showing the plan outline of all structures existing within, at a scale of 1:1000 and larger with sub-metre to centimeters
planimetric and geometric accuracy. With very high resolution remote sensing data of the order of 1m available in hand, it
is possible to prepare maps with high resolution spatial content. The present exercise demonstrates a method of preparing
a geometrically and planimetrically accurate urban cadastral map on very large scale for a small area of about 5 sq km. IKONOS
merged data with 1m resolution is used for the purpose. Mapping was done in conjunction with on-site measurements and sketches.
Guides are used to maintain shape symmetry and accuracy of buildings and other features. Working out cost of mapping per unit
area is another objective in the present exercise. For want of fully or semi-automatic methods of information extraction from
very high resolution remote sensing data, it is imperative that mapping should be carried out in conjunction with some on-site
measurements wherever necessary. 相似文献