共查询到20条相似文献，搜索用时 823 毫秒
1.
Poonam S. Tiwari H. Pande Ashwini Kumar Pandey 《Journal of the Indian Society of Remote Sensing》2009,37(2):223-231
Automatic road extraction from remotely sensed images has been an active research in urban area during last few decades. But
such study becomes difficult in urban environment due to mix of natural and man-made features. This research explores methodology
for semiautomatic extraction of urban roads. An integrated approach of airborne laser scanning (ALS) altimetry and high-resolution
data has been used to extract road and differentiate them from flyovers. Object oriented fuzzy rule based approach classifies
roads from high resolution satellite images. Complete road network is extracted with the combination of ALS and high-resolution
data. The results show that an integration of LiDAR data and IKONOS data gives better accuracy for automatic road extraction.
The method was applied on urban area of Amsterdam, The Netherlands. 相似文献
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Automatic Road Extraction from High Resolution Satellite Image using Adaptive Global Thresholding and Morphological Operations 总被引：2，自引：0，他引：2
Road network extraction from high resolution satellite images is one of the most important aspects. In the present paper, research experimentation is carried out in order to extract the roads from the high resolution satellite image using image segmentation methods. The segmentation technique is implemented using adaptive global thresholding and morphological operations. Global thresholding segments the image to fix the boundaries. To compute the appropriate threshold values several problems are also analyzed, for instance, the illumination conditions, the different type of pavement material, the presence of objects such as vegetation, vehicles, buildings etc. Image segmentation is performed using morphological approach implemented through dilation of similar boundaries and erosion of dissimilar and irrelevant boundaries decided on the basis of pixel characteristics. The roads are clearly identifiable in the final processed image, which is obtained by superimposing the segmented image over the original enhanced image. The experimental results proved that proposed approach can be used in reliable way for automatic detection of roads from high resolution satellite image. The results can be used in automated map preparation, detection of network in trajectory planning for unmanned aerial vehicles. It also has wide applications in navigation, computer vision as a predictor-corrector algorithm for estimating the road position to simulate dynamic process of road extraction. Although an expert can label road pixels from a given satellite image but this operation is prone to errors. Therefore, an automated system is required to detect the road network in a high resolution satellite image in a robust manner. 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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10m级分辨率卫星影像道路语义模型研究 总被引：1，自引：1，他引：0
道路模型是遥感影像自动/半自动道路提取中重点研究的内容。本文首先介绍了传统的影像道路模型并指出其中不足,从语义的角度阐述了建立道路语义模型的必要性,概述了10m级分辨率卫星遥感影像道路的表现特征,分析了遥感影像道路提取涉及的各层次语义信息,建立了面向10m级分辨率卫星遥感影像的道路语义模型,详细阐述了语义模型的实现过程。将语义模型应用于笔者开发的遥感影像道路提取系统,通过新疆阿图什Spot5多光谱遥感影像道路提取试验,验证了道路语义模型的有效合理性。 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
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针对南方复杂地区水稻遥感信息提取研究中机器自动学习分类研究较少、分类精度不高的问题,以福建省三明市建宁县溪口镇为研究区,基于GF-1号卫星影像,采用面向对象的随机森林遥感分类算法对研究区内水稻田信息进行提取。首先通过优化面向对象分割参数和随机森林分类模型参数,提取并调用了影像中的多种特征;再对光谱特征、植被指数特征、纹理特征、几何特征进行特征空间优选;最后通过设置4种特征优选试验进行对比,得到最优分类模型。实验结果显示,基于特征空间优选的面向对象随机森林分类算法的水稻提取精度高达90%,分类总体精度可达87%,Kappa系数为0.85;与其他试验结果相比,漏分和误分现象较少,实现了南方地区水稻信息高精度自动识别。该方法计算特征少、实现简便,对于国产高分卫星影像在南方复杂地区作物自动提取中的应用具有参考性。 相似文献
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Abolfazl Abdollahi Hamid Reza Riyahi Bakhtiari Mojgan Pashaei Nejad 《Journal of the Indian Society of Remote Sensing》2018,46(3):423-430
Currently, methods of extracting spatial information from satellite images are mainly based on visual interpretations and drawing the consequences by human factor, which is both costly and time consuming. A large volume of data collected by satellite sensors, and significant improvement in spatial and spectral resolution of these images require the development of new methods for optimal use of these data in order to produce rapid economic and updating road maps. In this study, a new automatic method is proposed for road extraction by integrating the SVM and Level Set methods. The estimated probability of classification by SVM is used as input in Level Set Method. The average of completeness, correctness, and quality was 84.19, 88.69 and 76.06% respectively indicate high performance of proposed method for road extraction from Google Earth images. 相似文献
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Fuzzy Logic System for Road Identification Using Ikonos Images 总被引：1，自引：0，他引：1
Jalal Amini Caro Lucas Mohammad Saradjian Ali Azizi & Saeed Sadeghian 《The Photogrammetric Record》2002,17(99):493-503
Research into both extraction of man-made objects and automatic change detection from aerial and satellite images has made significant progress in recent years. This paper presents an approach, based on a fuzzy logic system, for the identification of suburban roads in Ikonos images. The linguistic variables are the mean and standard deviation (SD) of different objects with Gaussian membership function. After the roads have been identified provisionally and their skeleton extracted, the skeleton can be vectorised and then used as direct input to a GIS for further analysis. The method was tested on an Ikonos "Geo" image covering Bilesavar in north-western Iran. For the suburban area of Bilesavar, the results showed that grey scale values ranged from 20 to 190 for non-roads and 226 to 228 for roads, the optimum width of the Gaussian kernel function was 3 and the SD was 0.4. It was also found that about 91% of main roads with a width of 6 to 12 pixels could be extracted from high resolution satellite imagery by the algorithm. The computer program for this study has been developed in visual C++ based on Windows 98 相似文献
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Hatice Catal Reis Bülent Bayram Salih Bozkurt Abdulkadir Ince Nusret Demir Dursun Zafer Seker 《Journal of the Indian Society of Remote Sensing》2018,46(8):1223-1232
This study presents an extended shoreline detection approach from pansharpened images of Turkish RASAT satellite which covers red, green and blue bands of the optical spectrum with 15 m ground resolution and panchromatic band with 7.5 m spatial resolution. The Lake Ercek of Turkey has been selected as the study area, which is a tectonic lake and home to a variety of water birds. The satellite images of the lake taken in 2013 and 2014 were considered for analysis. The proposed shoreline extraction system consists of a sequence of image processing steps in which simple linear clustering (SLIC) and particle swarm optimization (PSO) are the main components. SLIC was used to create superpixels that form basis for object-based image analysis while PSO was employed for classifying objects into corresponding classes. The resulting images still contained unwanted artefacts; therefore, a post-processing step was performed to improve the accuracy of segmentation by applying thresholding, morphological processing, and manual editing for noise removal. The proposed framework was applied on two temporal RASAT images to test the variations of defined parameter settings. The success of the proposed system was to obtain shorelines with satisfying accuracy without using NIR band. Finally, the extracted shorelines were vectorised and compared with manually digitized shorelines from pansharpened satellite images for accuracy assessment. 相似文献
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针对顶点成分分析方法无法实现复杂地表环境下的高光谱影像端元精确提取问题,提出了一种基于空谱协同多尺度顶点成分分析的端元提取方法,通过影像空谱特征融合和聚类分割,对不同分辨率空间尺度下的分割影像进行端元协同提取,并考虑噪声对影像端元提取精度的影响,提升端元提取的精度。首先,对影像进行预处理,采用低秩矩阵分解去除噪声。其次,对高光谱影像进行空谱多特征提取,利用多特征融合和K-means算法进行聚类分割,获取地物分布的空间异质性信息,提升后续端元提取的精度。然后,对高分辨率影像空间降采样,利用顶点成分分析方法对降采样后的低分辨率分割图像进行端元提取,并利用坐标映射寻找高分辨率影像中的相应端元,利用光谱角来判定是否为纯端元。最后,遍历上述方法至所有分割影像以获取最终的端元集合。使用模拟数据和真实的高分五号高光谱数据对提出的方法进行实验验证。实验结果表明,空谱协同多尺度顶点成分分析方法可提取高精度的纯净端元,且计算效率较高。 相似文献
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安丽 《测绘与空间地理信息》2018,(3):116-117,120
Hough变换方法是高分辨率遥感影像中提取直线道路的鲁棒性较好的方法。本文采用基于连通域的图像分割技术优化Hough算法,在Matlab环境中进行复杂场景下道路提取实验,实验证明:改进算法能有效进行复杂场景下道路边缘的提取,降低参数数量,提高运算速率,改善道路提取效果。 相似文献
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矢量数据辅助的高分辨率遥感影像道路自动提取 总被引：1，自引：0，他引：1
高分辨率遥感影像上细节信息繁杂、干扰物普遍存在,对其进行自动化道路识别与提取的相关研究仍处在探索阶段。在道路提取过程中引入矢量数据辅助,可解决初始信息获取的困难,得到可靠性较强的训练样本。为此,提出一种矢量数据辅助下的道路提取方法,能够筛选出矢量数据中包含的有效信息,引导实现对高分辨率遥感影像的道路自动提取。利用Mean-shift滤波对图像进行预处理后,首先从矢量数据获取候选种子点,并通过提炼同质区域的形状特征剔除错误候选点;然后,自动获取负样本点以进行朴素贝叶斯分类,并采用邻域质心投票算法从分类影像提取道路中心线;最后,结合像素跟踪与方向判断矢量化道路中心线,并提出一种基于矢量几何分析的断线连接与毛刺剔除方法,对提取结果进行信息修复与规整、优化。实验结果显示,该算法的提取质量达到80%以上,且具备较强的稳健性,能够适应具有不同道路辐射和分布特征的高分辨率遥感影像。 相似文献
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Contourlet变换和Tsallis熵的多源遥感图像匹配 总被引：1，自引：0，他引：1
提出了一种利用Contourlet变换、Tsallis熵和改进粒子群优化的多源遥感图像匹配算法。在分别对参考图像和目标图像进行Contourlet分解的基础上,以基于Tsallis熵的互信息量作为相似性度量准则,利用改进的带极值扰动的简化粒子群优化算法对低分辨率的遥感图像进行匹配操作,逐级上推,最终实现全分辨率情况下多源遥感图像的匹配。实验结果表明,与常用的遥感图像匹配算法相比,该算法匹配精度高,稳健性好,且运算量大幅减少。 相似文献
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在高分辨率遥感影像中提取无清晰连续边缘线的道路 总被引：4，自引：0，他引：4
现有的许多道路提取算法均利用道路的外边缘线信息来实现道路的提取,当边缘线清晰连续时,采用这些方法都可以取得很好的提取效果.不过,在高分辨率的城市遥感影像中,常常会存在一些低对比度区域,处于其中的道路边缘线非常之弱,以致难以直接检测出单个的边缘点.如果受到树木、房屋及车辆的干扰,这些原本就很弱的边缘还会发生断裂.通过现有方法提取具有如此边缘线的道路难度很大.本文给出一种旨在解决这一问题的新方法.首先借鉴相位编组原理形成边缘线支持区并对其进行连接;然后利用动态规划方法从支持区中检测出边缘线并对这些线进行平滑;最后连接由边缘线构成的道路段,得出道路提取结果.实验表明,本方法可以较好地提取出无清晰连续边缘线的道路,对于边缘对比度较大的道路则可取得更为令人满意的结果. 相似文献
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针对天绘一号卫星高分辨率影像,采用面向对象分类方法对怀柔水库区域进行水体信息提取,在多尺度分割的基础上,统计地物的光谱信息、形状因子和亮度均值等,建立水体信息的特征集,充分利用高分辨率的特点提取水体信息,同时选取了参数相近的SPOT和RapidEye两幅国外高分影像进行对比研究,使用相同方法进行水体提取,对实验过程和结果进行了对比分析。针对提取结果,采用野外采样和矢量图分析两种方法综合进行精度评价,根据采样数据得到的精度分别为96.97%,95.45%,92.42%,分析实验结果的矢量图,其中天绘影像水体提取面积为5 537 412.5㎡,SPOT影像为5 398 225㎡,RapidEye影像为5 053 262.5㎡,对实际水域的面积覆盖分别达到了101.40%,98.85%,92.54%,天绘影像的整体精度较高,但在细节表现上较为模糊,主要误差来自于对湿地的误分。实验制定了适用于天绘影像的水体提取方法和规则,分析不同因素对分割与分类结果的影响,同时,我们比较了天绘影像与国外同级别高分影像的优劣性,为天绘影像的进一步应用提供了参考。 相似文献
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ZHANG Yi YAN Li 《地球空间信息科学学报》2007,10(4):276-281
A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automati... 相似文献