Stereo analysis of high-resolution SAR images for building height estimation in cases of orthogonal aspect directions

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.     

An Adaptive and Iterative Method of Urban Area Extraction From SAR Images

This letter presents a new method for unsupervised urban area extraction from synthetic aperture radar (SAR) images based on the ffmax algorithm proposed by C. Gouinaud specially for acquiring urban areas in SPOT imagery. According to the statistical characteristics of urban areas, an adaptive and iterative method based on the low-level extraction given by the ffmax algorithm using a large window is proposed. Experimental results on real SAR images show that the proposed automatic method works quickly and can preserve the borders of urban areas as well as avoid the disturbance of other classes and the extractions of urban areas are reliable and precise     

基于数学形态学和相位编组SAR影像道路自动提取

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。     

一种从SAR图像中提取城市道路网络的方法

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.     

DEM Reconstruction in Layover Areas From SAR and Auxiliary Input Data

In this letter, a methodology to overcome the layover problem and obtain the 3-D reconstruction of urban areas will be discussed. Interferometric synthetic aperture radar (SAR) (InSAR) systems allow the estimation of height profiles of the Earth surface, but in the case of urban scenarios, estimation becomes a hard task due to the presence of SAR geometrical distortions, with layover above all. First, the layover signal in InSAR images is investigated; then, a procedure to specifically manage layover areas is presented. The proposed method consists of introducing an auxiliary data exploitation, optical data or SAR shadowing, in the maximum a posteriori statistical estimation technique to improve the digital elevation model reconstruction, particularly on phase discontinuities. We test the method on simulated data, showing its effectiveness.     

高分辨率SAR与光学遥感影像中道路提取方法的研究

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...     

Comparative Study on the Performance of Multiparameter SAR Data for Operational Urban Areas Extraction Using Textural Features

The advent of a new generation of synthetic aperture radar (SAR) satellites, such as Advanced SAR/Environmental Satellite (C-band), Phased Array Type L-band Synthetic Aperture Radar/Advanced Land Observing Satellite (L-band), and TerraSAR-X (X-band), offers advanced potentials for the detection of urban tissue. In this letter, we analyze and compare the performance of multiple types of SAR images in terms of band frequency, polarization, incidence angle, and spatial resolution for the purpose of operational urban areas delineation. As a reference for comparison, we use a proven method for extracting textural features based on a Gaussian Markov Random Field (GMRF) model. The results of urban areas delineation are quantitatively analyzed allowing performing intrasensor and intersensors comparisons. Sensitivity of the GMRF model with respect to texture window size and to spatial resolutions of SAR images is also investigated. Intrasensor comparison shows that polarization and incidence angle play a significant role in the potential of the GMRF model for the extraction of urban areas from SAR images. Intersensors comparison evidences the better performances of X-band images, acquired at 1-m spatial resolution, when resampled to resolutions of 5 and 10 m.      

多源数据协同的城市道路提取

城市道路的高精度提取可为城市三维表达、城市地形分析、城市建设规划、交通导航等提供数据基础和支撑。本文以合肥市局部城区为试验区,以开源路网、街景图像和遥感影像为数据源,在利用最大似然法进行初提取的基础上,通过空间分析、统计分析、几何量测、最小二乘拟合等方法进行粘连分割、缺失处理和交叉口细化等关键处理,构建了多源数据协同的城市道路提取方法,并对提取结果进行了精度评价和分析。试验结果表明,本文提出的城市道路提取方法优于最大似然和面向对象方法,提取总体精度为96.65%,Kappa系数为93.71%,道路宽度偏离标准差为0.03m,特别是对同物异谱、同谱异物及遮挡等造成的信息提取不全问题具有良好的改善效果。     

联合星载光学与SAR图像的城市大面积建筑物高度快速提取

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。     

改进剖面匹配和EKF对SAR影像道路半自动提取

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。     

Azimuth resolution of spaceborne P, VHF-band SAR

A degradation of spatial resolution performance of spaceborne synthetic aperture radar (SAR) images, which is due to the atmospheric radio waves propagation effects, is considered in this letter. A special calculation procedure of spatial resolution performances, in particular of the SAR azimuth resolution, is offered. Herein, the analysis of a potential spatial resolution, resulting from the influence of the atmosphere, on SAR images is presented.     

Automatic urban road extraction using airborne laser scanning/altimetry and high resolution satellite data

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.     

基于链码优化的SAR影像城市道路网络提取

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.     

<Emphasis Type="Italic">3D</Emphasis> Modelling of Urban Area Using Synthetic Aperture Radar (SAR)

Synthetic aperture radar (SAR) is a newly-developed remote sensing technology that works in all weather and independent of daylight. Recent satellite designs such as TerraSAR-x, which have resolutions of a couple of meters and sub-meters, have provided appropriate data for modelling and monitoring of urban areas. Image classification and height information extraction is possible considering the nature of SAR data. In this paper, a proper classification method for high-resolution SAR images has been used in urban areas. This classifier is based on statistical models. First, statistical models that are well adapted to urban SAR images are selected. Initial labelling is performed using the maximum likelihood method. A method based on Markov random fields is applied to improve the results by considering neighbourhood information. Meanwhile, topographic information is extracted using the phase difference obtained from SAR interferometry. After classification and height extraction, the homogeneous regions consisting of locations with similar objects are determined. The homogeneous region adjacency graph are generated using vectors containing classification information, extracted objects, height of pixels forming each region, and information on the neighbouring areas. Height and classification information are then merged by assigning height conditions based on the nature of objects and optimizing an energy function. The results obtained, including buildings, streets, and corner reflectors, are easily recognizable. The overall accuracy is improved from 57% in the initial classification to 95% in the employed procedure. Moreover, the accuracy of height estimation is about 2.74 m, which is acceptable for height estimations of buildings with more than one floor.     

Automatic main road extraction from high resolution satellite imageries by means of particle swarm optimization applied to a fuzzy-based mean calculation approach

Manual extraction of road network by human operator is an expensive and time-consuming procedure. Alternatively, automation of the extraction process would be a great advancement. For this purpose, an automatic method is proposed to extract roads from high resolution satellite images. In this study, using few samples from road surface, a particle swarm optimization is applied to a fuzzy-based mean calculation system to obtain road mean values in each band of high resolution satellite colour images. Then, the images are segmented using the calculated mean values from the fuzzy system. Optimizing the fuzzy cost function by particle swarm optimization enables the fuzzy approach to be the best mean value of road with sub-grey level precision. Initially, this method was applied to simulated images where the calculated mean values are consistent with the hypothetic mean values. Application of the method to IKONOS satellite images has shown a prospective outcome for automatic road extraction. Mathematical morphology is subsequently used to extract an initial main road centreline from the segmented image. Then, small redundant segments are automatically removed. The quality of the extracted road centreline indicates the effectiveness of the proposed approach.     

Application of the RPC model for spaceborne SAR image geometric processing

An increasing number of low, medium, and high resolution SAR satellites creates a demand for a generalized sensor model to replace the rigorous sensor model (RSM). The rational polynomial coefficient (RPC) model is a generic sensor model which accurately fits the object-image geometry for various sensor systems with different coefficient values. It has been widely used as an alternative to RSM for photogrammetric processing of optical images, but its applications to SAR images are rarely discussed in publications. In this paper, the feasibility and practicability of the RPC model for SAR images are studied. The RPC model can not only be used to replace the RSM (range–Doppler model for SAR), but also applied to the processing chain for SAR data, thus facilitating the processing of SAR and InSAR data for end users.     

玉树地震灾情SAR遥感监测与信息服务系统

在玉树地震中,中国首套自主知识产权的机载多波段多极化干涉SAR测图系统,发挥全天时主动遥感的优势,成功服务于抗震救灾中。依据玉树地震灾情综合地理信息监测与评估工作,着重探讨SAR遥感影像用于地震灾情监测与评估中的处理方法和技术路线,研究制定了地震灾区灾情综合地理信息监测指标,通过快速几何处理、快速变化信息提取、快速目标判读和灾害空间危险性评估,实现了玉树地震震区灾情综合地理信息的解译、制图和统计评估。在此基础上,开发了玉树地震灾情综合地理信息服务系统,实现了灾情监测信息的综合管理、可视化查询和统计分析。     

Extracting urban water bodies from high-resolution radar images: Measuring the urban surface morphology to control for radar’s double-bounce effect

Satellite remote sensing is an effective method for extracting water bodies on a large scale. Radar imagery, such as synthetic aperture radar (SAR) imagery, can penetrate clouds and provide opportunities for water body identification when in situ observations are difficult to obtain because of severe weather conditions. However, when using SAR images in urban areas to extract water bodies, the radar’s double-bounce effect results in complicated backscatter patterns of water near urban features such as buildings due to the side-looking properties of SAR sensors and the vertical urban structures. Therefore, the objective of this study is to propose a reliable urban water extraction framework for SAR images that integrates urban surface morphological features for controlling radar’s multiple bounces. Statistical (logistic regression) and machine-learning (random forest) models were used to explore how radar’s double-bounce effect influences the prediction performance of urban water extraction. Our findings indicate that when extracting urban water bodies, urban water’s backscatter values could be significantly interfered by the neighboring building density above a threshold height that contributes to radar’s multiple bounces. Without model calibration, our framework incorporating urban surface morphology demonstrates high prediction ability with an Area Under the Curve (AUC) of 0.914 and with 97.0% of urban water cells correctly identified by testing in another city sharing similar urban forms. In summary, our study provides a better understanding of the role of the urban surface morphology in the double-bounce effect in SAR images, specifically for differentiating urban water and land, thereby improving the accuracy of urban water extraction and enhancing the feasibility of further applications of SAR imagery under complex urban landscapes.     

Road Network Extraction from High-Resolution Remote Sensing Image Using Homogenous Property and Shape Feature

According to spectral homogeneity and ribbon-like shape of road, this letter presents a simple yet effective method of delineating road networks from high-resolution remote sensing images. The proposed method consists of three main steps. First, the mean shift algorithm is utilized to detect the modes of density of image points in spectral–spatial space which contain potential road center points and then detected mode points are classified into different classes by mean shift-based clustering on the basis of spectral information. Next, the combination of Gabor filtering and tensor encoding is used to identify the road class and to extract road center points. Lastly, road network is generated from detected road center points by means of tensor voting and connected component analysis. The experimental results demonstrate good performances of the proposed method in road network extraction from high-resolution remote sensing images.     

基于灰度和方向一致性的遥感影像道路网提取

从遥感影像中提取道路网是一个经典课题,根据遥感影像中的道路具有灰度和方向一致性的特征,提出一种从遥感影像中提取道路网的新方法。首先根据遥感影像的灰度信息和方向方差信息建立灰度和方向一致性准则分割模型,由此可从遥感影像中提取基本的道路网轮廓,然后再针对道路区域存在非道路点:空洞和裂缝等情况,采用膨胀、腐蚀等操作去除杂乱物块,最后通过数学形态学操作提取出道路网。实验结果表明,该方法能够适用道路、建筑物、植被等多种复杂地物的城市遥感影像中提取道路网,且能获得较好地提取效果。