共查询到20条相似文献，搜索用时 910 毫秒
1.
道路提取作为典型的线状目标提取,是遥感影像目标解译的研究热点。合成孔径雷达（SAR）影像包含了丰富的物理特性,能够全天时、全天候地获取影像数据,已广泛应用于道路提取中。传统的道路提取方法分为全自动和半自动方法。全自动道路提取会出现漏检和错检,需要大量的人工后处理。半自动方法结合人工干预,是对计算机的计算能力和人工解译准确性的有效折中。提出了用一种改进剖面匹配和扩展卡尔曼滤波（EKF）的方法对SAR影像道路进行半自动提取的方法。首先构建了道路提取模型,其次通过改进剖面匹配算法获取准确的观测值,最后利用EKF对观测值进行更新获取道路最优估计值。选取美国缅因州Howland地区L波段UAVSAR数据和海南陵水地区X波段机载SAR数据进行实验,结果表明,该方法在较少人工干预的情况下,能够对复杂场景道路进行有效稳健的提取。 相似文献
2.
针对高分辨率SAR影像中细节信息损坏道路的面特征结构、影响道路提取,基于影像统计特征,给出一种结合区域生长和细节信息识别的道路提取方法。该方法通过区域生长提取呈现面特征的暗目标(道路框架),利用CFAR算法识别细节,通过形态学融合得到最终结果。为降低高分辨率影像区域异质性对提取结果影响,提出了一种自适应CFAR算法,相比之前算法可自适应删除干扰点;并引入有效表征影像统计的GA0分布。利用海南省陵水黎族自治县机载X波段高分辨率SAR数据的幅度影像进行实验,结果表明,该方法能有效提取呈面特征的道路,获得准确的道路宽度和中心线信息。 相似文献
3.
Improving urban road extraction in high-resolution images exploiting directional filtering, perceptual grouping, and simple topological concepts 总被引：1，自引：0，他引：1
In this letter, the problem of detecting urban road networks from high-resolution optical/synthetic aperture radar (SAR) images is addressed. To this end, this letter exploits a priori knowledge about road direction distribution in urban areas. In particular, this letter presents an adaptive filtering procedure able to capture the predominant directions of these roads and enhance the extraction results. After road element extraction, to both discard redundant segments and avoid gaps, a special perceptual grouping algorithm is devised, exploiting colinearity as well as proximity concepts. Finally, the road network topology is considered, checking for road intersections and regularizing the overall patterns using these focal points. The proposed procedure was tested on a pair of very high resolution images, one from an optical sensor and one from a SAR sensor. The experiments show an increase in both the completeness and the quality indexes for the extracted road network. 相似文献
4.
高分辨率影像能够提供丰富的地表细节信息,从高分辨率遥感影像中进行高精度的道路提取是目前遥感信息处理的研究热点。分别以高分辨光学IKONOS影像和COSMO-Skymed SAR影像为数据源,对北京市某区域进行了道路信息自动提取方法的研究。高分辨率光学影像中采用最大似然分类进行道路信息提取,在SAR影像中则采用Otsu阈... 相似文献
5.
基于数学形态学和相位编组SAR影像道路自动提取 总被引：3，自引：1，他引：2
由于SAR图像中固有的斑点噪声的强烈影响,某些对于光学图像有很好效果的边缘检测算子,但是对于SAR图像来说,效果很差,本文应用一种改进的基于图像统计信息的局部线特征检测方法,首先利用图像统计信息对图像进行局部特征检测,然后利用数学形态学去除内部空隙并细化得到道路段,将道路段进行相位编组,进而自动提取出道路。 相似文献
6.
针对高分辨率SAR影像道路交叉口提取易受周围地物干扰的问题,设计了一种利用三角形检测模型提取道路交叉口的方法。该方法首先采取滤波与锐化消除道路交叉口区域噪声点并凸显道路边缘;接着根据灰度特征,通过形态学运算确定道路交叉口候选区域;最后在候选道路交叉口区域运用三角形检测模型,确认道路交叉口。使用3 m Tan DEM-X数据进行实验,结果证明算法对各种常见二维道路交叉口模型均有较好识别效果。 相似文献
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基于链码优化的SAR影像城市道路网络提取 总被引：1，自引：0，他引：1
针对传统的基于局部比率的道路提取算子存在道路展宽与定位精确性差的缺点,通过加入一个修剪窗口进行改进,有助于去除河流、树木等的影响,且得到了细化和定位更加准确的道路图谱.首次将链码用于道路连接表示,定义了链码能量网络,并将道路的先验知识引入,然后在对模拟道路图像线段连接概率分析的基础上得到了链码优化算法.由于该方法采用了分线运算,每次迭代不需要搜索整个道路片段,提高了运算效率.最后将该算法应用于真实SAR影像巾道路网络的提取,证明了它的有效性. 相似文献
9.
传统光学遥感技术手段在森林覆盖区难以准确获取林下地形,原因在于其只能测量森林冠层顶部高程。微波信号能够穿透森林冠层并记录森林垂直结构信息,为解决林下地形测绘难题带来了契机,如何准确获取林下地形已成为微波遥感领域的研究热点。首先介绍了面向林下地形测绘的合成孔径雷达（synthetic aperture radar,SAR）干涉测高原理及数据获取手段。然后对利用SAR进行林下地形测绘的方法进行了分类,主要包括基于合成孔径雷达干涉测量（interferometric synthetic aperture radar,InSAR）、极化合成孔径雷达干涉测量（polarimetric InSAR,PolInSAR）及基于多基线InSAR/PolInSAR数据的层析SAR（tomographic SAR,TomoSAR）技术的林下地形测绘方法,并介绍了上述3种方法的应用进展。最后在此基础上,从数据获取、误差改正及散射模型构建3个角度分析了林下地形测绘所面临的问题。 相似文献
10.
利用MRF方法的高分辨率影像道路提取 总被引：1，自引：0，他引：1
高分辨率遥感影像提供了地物更丰富的信息,包括光谱信息、地物结构、形状、纹理以及地物之间的空间关系等多方面的信息。面向对象的影像分析方法以目标地物为研究对象,充分考虑目标地物的形状、结构及空间关系等信息进行目标的提取和分析,是当前高分辨率信息提取技术的主要方法。研究了采用面向对象目标的思想将MRF方法应用于高分辨率遥感影像的道路目标提取中,并进行了道路提取实验。 相似文献
11.
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
12.
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
13.
光学传感器在夜晚和云雨天气难以成像,合成孔径雷达（synthetic aperture radar,SAR）虽然能够全天时、全天候工作,但其成像难以理解,对此提出利用SAR影像翻译为光学影像的新思路来弥补二者的缺陷。给出了遥感影像翻译定义,提出一套包含图像理解、目标转换等环节的影像翻译技术流程。通过支持向量机分类、种子填充和基于样本的纹理合成算法等手段实现SAR影像典型目标向光学影像的转换与表达。最后,利用该方法实现了ENVISAT-ASAR转换为Landsat TM,ALOS PALSAR转换为GeoEye的两类影像翻译,并利用SAR影像翻译结果修补光学影像空缺。影像翻译和补缺实验证明了SAR影像翻译为光学影像的可行性和有效性。 相似文献
14.
星载高分辨率光学图像与SAR图像广泛应用于城市建筑物高度提取,但光学图像存在缺少相关卫星参数的情况,而SAR图像则存在散射特征不完整以及提取效率低等缺陷。针对以上问题,本文提出一种联合高分辨率星载光学与SAR图像的城市大面积建筑物高度快速提取方法。首先,结合支持向量机(SVM)和形态学阴影指数(MSI)快速提取光学图像中的阴影并自动测量阴影长度;之后选择多个合适样本,基于模型匹配法从SAR图像中提取高度;最后将高度与阴影长度作线性回归分析,建立数学模型来提取其他建筑物的高度。该方法将不同卫星系统的数据和特征相结合,互相弥补各自缺陷,不仅提高了效率、降低了成本,同时满足精度要求。 相似文献
15.
一种从SAR图像中提取城市道路网络的方法 总被引：6，自引：0，他引：6
提出一种从高分辨率SAR图像中提取城市道路网络的算法.在高分辨率SAR图像中,道路在空间结构上表现为一细长的且宽度基本恒定不变的均匀区域.利用模糊C均值聚类方法对高分辨率SAR图像进行聚类分析,将道路类像素从原始图像中分离出来.为突出道路形状特征,减少冗余信息,对聚类结果进行细化,同时利用跟踪算子消除短线段;以提取道路中心线二值图的像素值作为图像能量,应用Snakes模型检测道路网络.通过实际SAR图像验证,该算法可以准确提取复杂的城市道路网络. 相似文献
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17.
In this paper, a novel change detection approach is proposed for multitemporal synthetic aperture radar (SAR) images. The approach is based on two difference images, which are constructed through intensity and texture information, respectively. In the extraction of the texture differences, robust principal component analysis technique is used to separate irrelevant and noisy elements from Gabor responses. Then graph cuts are improved by a novel energy function based on multivariate generalized Gaussian model for more accurately fitting. The effectiveness of the proposed method is proved by the experiment results obtained on several real SAR images data sets. 相似文献
18.
《International Journal of Digital Earth》2013,6(7):657-674
ABSTRACTAs an important advanced technique in the field of Earth observations, Synthetic Aperture Radar (SAR) plays a key role in the study of global environmental change, resources exploration, disaster mitigation, urban environments, and even lunar exploration. However, studies on imaging, image processing, and Earth factor inversions have often been conducted independently for a long time, which significantly limits the application effectiveness of SAR remote sensing due to the lack of an overall integrated design scheme and integrated information processing. Focusing on this SAR application issue, this paper proposes and describes a new SAR data processing methodology – SAR data integrated processing (DIP) oriented on Earth environment factor inversions. The simple definition, typical integrated modes and overall implementation ideas are introduced. Finally, focusing on building information extraction (man-made targets) and sea ice classification (natural targets) applications, three SAR DIP methods and experiments are conducted. Improved results are obtained under the guidance of the SAR DIP framework. Therefore, the SAR DIP theoretical framework and methodology represent a new SAR science application mode that has the capability to improve the SAR remote sensing quantitative application level and promote the development of new theories and methodologies. 相似文献
19.
Peter Doucette Peggy Agouris Anthony Stefanidis Mohamad Musavi 《ISPRS Journal of Photogrammetry and Remote Sensing》2001,55(5-6)
The extraction of road networks from digital imagery is a fundamental image analysis operation. Common problems encountered in automated road extraction include high sensitivity to typical scene clutter in high-resolution imagery, and inefficiency to meaningfully exploit multispectral imagery (MSI). With a ground sample distance (GSD) of less than 2 m per pixel, roads can be broadly described as elongated regions. We propose an approach of elongated region-based analysis for 2D road extraction from high-resolution imagery, which is suitable for MSI, and is insensitive to conventional edge definition. A self-organising road map (SORM) algorithm is presented, inspired from a specialised variation of Kohonen's self-organising map (SOM) neural network algorithm. A spectrally classified high-resolution image is assumed to be the input for our analysis. Our approach proceeds by performing spatial cluster analysis as a mid-level processing technique. This allows us to improve tolerance to road clutter in high-resolution images, and to minimise the effect on road extraction of common classification errors. This approach is designed in consideration of the emerging trend towards high-resolution multispectral sensors. Preliminary results demonstrate robust road extraction ability due to the non-local approach, when presented with noisy input. 相似文献