基于RPC模型的高分辨率SAR影像正射纠正

在分析TerraSAR-X、COSMO-SkyMed等高分辨率SAR影像成像几何模型的基础上,采用RPC模型拟合SAR影像的成像几何模型,拟合的精度在1%个像素以内;在1∶5万DRG上选取1个控制点对RPC模型参数精度的改进,结合1∶5万DEM对TerraSAR-X、COSMO-SkyMed数据进行正射纠正,纠正结果能满足1∶5万DOM的精度要求.从而说明RPC拟合雷达成像几何的正确性以及利用RPC模型进行高分辨率SAR影像正射纠正的可行性.     

利用光学遥感影像进行星载SAR影像正射纠正

基于角反射器点的正射纠正方法仅适用于局部区域的SAR影像,无法满足大区域生产和工程化需求的问题。本文采用有理函数模型（RFM）作为星载SAR几何模型,利用资源三号测绘卫星的数字表面模型（DSM）产品和数字正射影像图（DOM）,选取遥感13号SAR影像与资源三号光学影像的同名像点作为控制点,对遥感13号SAR影像进行了正射纠正,并与常规的基于角反射器点的正射纠正方法进行了对比分析。试验结果表明,针对平原地区的遥感13号SAR影像,在四角布设控制点的情况下,基于角反射器点的正射纠正方法比基于光学正射影像的正射纠正方法精度高,正射纠正精度分别优于2.5和4.5 m。     

“天绘一号”影像正射纠正实验与精度分析

针对如何有效提高"天绘一号"卫星影像正射纠正精度的问题,本文基于有理函数模型,提出RPC参数+像方误差补偿方案,利用控制点提高RPC模型的精度。通过对连云港、怀柔地区"天绘一号"卫星影像进行正射纠正,对比无控纠正结果验证该方案。实验结果表明:利用RPC模型进行影像正射纠正是正确的、有效的,辅以稀少控制点就能获得较高精度,不使用任何控制点将会导致系统误差偏大,精度较低。本文研究可为修正卫星影像自带RPC参数误差、提高正射纠正精度提供参考。     

基于多项式正射纠正模型的机载SAR影像区域网平差

在SAR影像多项式正射纠正模型基础上,分别对平高点、平面点、高程点、加密点列出了误差方程,从而建立了基于多项式正射纠正模型的机载SAR影像区域网平差模型,并设计了相应的软件.利用成都测区的机载SAR影像进行了实验,取得了比较满意的结果.     

基于有理函数“天绘一号”影像无控制正射纠正

文中根据影像正射纠正的基本原理和方法,利用有理函数模型和天绘一号三线阵影像自身生成的DEM数据,实现天绘一号影像的正射纠正,并依据无控制条件下的影像纠正精度估算公式对影像正射纠正精度进行估算,按此方法在东北区域制作DOM,然后利用天绘一号卫星摄影参数检测场的航空影像成果对纠正的精度进行验证,实验结果表明,在天绘一号三线阵影像生成的DEM支持下进行天绘一号影像正射纠正具有较高的精度,能够满足制作1∶5万正射影像精度的要求。     

三调正射影像生产中道路扭曲的快速纠正方法

土地调查中数字正射影像(DOM)底图生产是开展资源与环境监测、国情普查的基础.针对正射纠正后影像中存在大量扭曲区域,特别是道路区域,本文提出全新作业模式,即通过编辑道路扭曲区域数字高程模型(DEM),进行实时局部正射纠正来实现.高分辨测绘卫星影像高分二号和北京二号两组实验数据生产表明,该方法实现了影像道路扭曲区域的快速纠正,纠正后道路区域边缘地物没有出现明显错位现象.同时,一定数量道路区域控制点的局部纠正前后精度对比,表明该方法很大程度提高了道路扭曲区域的纠正精度,平面精度优于4 m,满足我国1:1万正射影像生产精度要求.      

基于DEM和查找表的高分辨率机载SAR图像正射校正

山区SAR图像的正射校正受成像几何影响存在较大畸变,实现无控制点的正射校正是一难点。本文提出基于DEM和RD模型来模拟SAR图像为基础,同时创建与DEM的地理坐标相一致的查找表,将模拟成像过程中DEM地理坐标与SAR图像坐标之间的RD模型映射关系采用查找表记录。经过模拟图像与真实图像的精确配准,DEM所在的空间三维坐标与真实SAR图像二维坐标实现了关联。实验选择了一景高分辨率的机载SAR图像和高分辨率的DEM数据,实验结果表明：本方法无需地面实测控制点,可以有效地正射校正高分辨率的机载SAR图像,平面位置与DEM平面坐标完全一致,精度在一个像素以内。该方法简单易于实现,除了模拟图像与真实图像需要人工半自动化的配准,在后续处理中均为自动化处理。校正结果受SAR成像特征所限,仅在透视收缩、叠掩区域存在辐射误差。     

SPOT HRG影像无控制正射纠正实验与精度分析

本文根据影像正射纠正的基本原理和方法,提出了无控制点条件下的影像正射纠正理论估算公式,并据此公式对无控制条件点下的影像进行正射纠正理论精度估算,表明了在SRTMDEM支持下进行SPOT影像正射纠正具有较高的精度。并按此方法对杭州、重庆和大庆三个不同地形的区域制作DOM,然后利用我国1:1万地形图对其进行精度评定,实验结果证明正射纠正精度估算公式正确,同时利用SRTMDEM对SPOTHRG进行正射纠正得到的影像能够满足1:50000测图精度的要求。     

基于影像模拟的星载SAR影像正射纠正

对山地和高山地等选点困难地区的星载SAR影像进行正射纠正时,通常采用距离多普勒模型进行影像模拟纠正。但由于每类星载SAR影像辅助数据不同,所建立的距离多普勒模型均不相同,从而导致针对每类星载SAR影像需要采用不同的软件模块进行模拟和正射纠正。针对该缺点,采用RPC模型代替距离多普勒模型并利用改进的模拟影像灰度确定方式进行星载SAR影像模拟,在此基础上建立模拟影像和真实SAR影像之间关系进行正射纠正。采用四川某地区的TerraSAR-X影像,将正射纠正的实际精度和理论精度进行对比,验证本文提出的理论和方法。     

京津冀地区高分一号宽覆盖正射影像生成

针对高分一号宽覆盖1A级影像的大区域正射影像生成后,相邻影像接边精度不高的问题,提出利用数字高程模型(DEM)作为高程约束的平面区域网平差方法提高其对地目标定位精度。通过京津冀地区的高分一号宽覆盖影像的平面区域网平差并进行正射纠正试验,在GOTOPO30 DEM的支持下,采用的区域正射纠正方法和处理流程取得了较好的效果。     

浅谈数字正摄影像的制作技巧与心得

数字正射影像图(DOM)是利用DEM对经过扫描处理的数字化航空像片或遥感数字影像(单色或彩色),经逐像元进行辐射改正、微分纠正和镶嵌,并按规定图幅范围裁剪生成的正射影像数据,并带有公里格网、图廓(内、外)整饰和注记的平面影像地图。DOM同时具有地图几何精度和影像特征的图像。具有信息丰富、形象逼真、获取快捷等优点,可作为地图分析背景控制信息,也可从中提取自然资源和社会经济发展的历史信息或最新信息,为城市规划等应用提供可靠依据。还可从中提取和派生新的信息,实现地图的修测更新。     

Study of dems derived from ERS-1/2 SAR and SRTM data

The DEM of the Bhuj earthquake affected area of 50 x 50 km was generated using the ERS-1/2 SAR tandem data (May 15—16,1996). Region growing algorithm coupled with path following approach was used for phase unwrapping. Phase to height conversion was done using D-GPS control points. Geocoding was done using GAMMA software. A sample data of DEM of Shuttle Radar Topography Mission (SRTM) of the Bhuj area is made available by DLR Germany. The intensity image, DEM and Error map are well registered. The spatial resolution of this DEM is about 25 m with height accuracy of a few meters. The DEM derived through ERS SAR data is prone to atmospheric affects as the required two images are acquired in different timings where as SRTM acquired the two images simultaneously. An RMS height error of 12.06 m is observed with reference to SRTM though some of the individual locations differ by as much as 35 m.     

利用DEM进行SAR图像模拟及地形辐射校正

在山区获取地面控制点比较困难,运用模拟SAR进行配准、校正,具有较大的优势。本文在分析SAR成像几何结构及ALOS PALSAR卫星轨道参数特征的基础上,运用RD定位模型对DEM的每个网格点进行雷达成像点的位置计算,模拟SAR图像,并提取当地入射角、投影角及规则化因子等;模拟出的SAR图像与真实SAR图像纹理吻合,有利于控制点的自动配准。在此基础上对ALOS PALSAR进行编码,构建基于规则化因子及入射角的地形辐射校正模型,消除面积效应及地形起伏造成的畸变问题,从结果中分析,校正后的图像明暗差异明显减少,这对雷达定量反演研究具有一定的现实意义。     

DEM and SAR image based flood feature extraction techniques to map the deep and shallow flood inundated regions of known as well as remote disaster regions

It is viable to differentiate the deep and shallow flood inundated regions through a new flood feature extraction techniques named as ‘Digital Elevation Model (DEM) and Synthetic Aperture Radar (SAR) image based flood feature extraction model’. The proposed model has been built mainly on the top of DEM of the disaster region without adopting standard multi-layer GIS techniques. To meet the time related factors of flood early warning system the image clustering operations has been automated at three different levels which bifurcates the input datasets and extracts the much required end results such as deep flooded regions, shallow flood inundated regions and non-flooded regions. The model has been tested with SAR flood images of known geographical region as well as remote geographical region. The proposed model can be automated against the input SAR sensor image and corresponding DEM of the respective SAR scene of any part of the world.     

基于有理多项式模型的星载高分InSAR影像制作数字高程模型的研究

合成孔径雷达干涉测量是一种利用SAR影像复数据的相位信息提取地面三维信息的技术,它通过获取地面目标在两幅SAR影像上的相位差值来解算该点的三维坐标。有理多项式（RPC,Rational Polynomial Coefficient）模型作为一种数学意义上的几何模型,它独立于传感器和平台,简单且具有通用性,可建立地面任意坐标与影像空间的关系。本文在RPC模型用于替代星载SAR的距离多普勒模型和星载InSAR的干涉相位方程基础上,研究 RPC模型应用于星载高分辨率InSAR影像制作DEM的可行性和精度。利用兰州COSMO-SkyMed数据和资源三号三线阵数据制作的DEM为参考数据进行实验验证,RPC模型用于InSAR技术生成的DEM,中误差为7.55米。     

Iteration convergence condition modeling for single spaceborne SAR image direct positioning

Single SAR image direct positioning is to determine the ground coordinate for each pixel in the SAR image assisted with a reference DEM. During this procedure, an iterative procedure is essentially needed to solve the uncertainty in elevation of each pixel in the SAR image. However, such an iterative procedure may suffer from the problem of divergence in shaded and serious layover areas. To investigate this problem, we performed a theoretical analysis on the convergence conditions that has not been intensively studied till now. The Range-Doppler (RD) model was simplified and then the general surface is degenerated into a planar surface. Mathematical deduction was then carried out to derive the convergence conditions and the impact factors for the convergence speed were evaluated. The theoretical findings were validated by experiments for both simulated and real scenarios.     

基于图像特征的星载SAR图像模拟研究

SAR图像模拟技术被广泛应用于SAR系统的设计和验证、SAR图像的正射纠正、雷达图像解译和目标识别等。随着星载SAR的发展,必然面临着对星载SAR图像模拟的大量需求。本文首先从SAR图像的几何特征和辐射特征出发,探讨了SAR图像模拟技术的原理,分析了RD（Rang Doppler）模型,后向散射模型和斑噪模型。在传统RD模型的基础上,根据不同地形特征（起伏地形和平坦地形）考虑不同的后向散射模型。特别强调了在平坦地形情况下,需要地物分类数据的参与,并利用Ulaby和Dobson的后向散射模型。另外,在SAR图像统计特征的基础上,进行SAR图像的乘性噪声模拟,可以满足更逼真的SAR场景需求。然后,给出了图像模拟的算法流程,并对关键步骤的算法做了分析。最后,在实现基于图像特征的星载SAR图像场景模拟算法的基础上,选择新疆窝依牙地区和天津地区分别进行起伏地形和平坦地形的模拟试验,实验结果证明了本文模拟算法的有效性。     

Orthorectification of VHR optical satellite data exploiting the geometric accuracy of TerraSAR-X data

Orthorectification of satellite data is one of the most important pre-processing steps for application oriented evaluations and for image data input into Geographic Information Systems. Although high- and very high-resolution optical data can be rectified without ground control points (GCPs) using an underlying digital elevation model (DEM) to positional root mean square errors (RMSEs) between 3 m and several hundred meters (depending on the satellite), there is still need for ground control with higher precision to reach lower RMSE values for the orthoimages. The very high geometric accuracy of geocoded data of the TerraSAR-X satellite has been shown in several investigations. This is due to the fact that the SAR antenna measures distances which are mainly dependent on the terrain height and the position of the satellite. The latter can be measured with high precision, whereas the satellite attitude need not be known exactly. If the used DEM is of high accuracy, the resulting geocoded SAR data are very precise in their geolocation. This precision can be exploited to improve the orientation knowledge and thereby the geometric accuracy of the rectified optical satellite data. The challenge is to match two kinds of image data, which exhibit very different geometric and radiometric properties. Simple correlation techniques do not work and the goal is to develop a robust method which works even for urban areas, including radar shadows, layover and foreshortening effects. First the optical data have to be rectified with the available interior and exterior orientation data or using rational polynomial coefficients (RPCs). From this approximation, the technique used is the measurement of small identical areas in the optical and radar images by automatic image matching, using a newly developed adapted mutual information procedure followed by an estimation of correction terms for the exterior orientation or the RPC coefficients. The matching areas are selected randomly from a regular grid covering the whole imagery. By adjustment calculations, parameters from falsely matched areas can be eliminated and optimal improvement parameters are found. The original optical data are orthorectified again using the delivered metadata together with these corrections and the available DEM. As proof of method the orthorectified data from IKONOS and ALOS-PRISM sensors are compared with conventional ground control information from high-precision orthoimage maps of the German Cartographic Survey. The results show that this method is robust, even for urban areas. Although the resulting RMSE values are in the order of 2-6 m, the advantage is that this result can be reached even for optical sensors which do not exhibit low RMSE values without using manual GCP measurements.     

组合图像模拟和精配准的星载SAR图像正射校正

本文给出了一种采用DEM模拟出的影像和星载合成孔径雷达(SAR)精配准策略的正射校正方法。首先根据DEM数据采用距离-多普勒模型和经验公式模拟出SAR图像,然后分别采用Harris算子和互信息匹配的方法提取模拟图像和实际SAR图像上的同名特征点,并根据这些特征点构建的不规则三角网(TIN)实现模拟SAR图像和实际SAR图像的精确配准。最后将星载SAR图像通过实际图像和模拟图像的精确配准关系以及模拟图像和DEM数据之间的对应关系校正到DEM所在的地理坐标中,实现SAR图像的正射校正。     

不同格网密度的DSM/DEM对影像分类精度的影响研究

在无控制点的卫星影像正射校正中,大多采用DSM/DEM数据作为辅助数据来消除或限制因地形起伏引起的形变,然而经不同格网密度的DSM/DEM正射校正后的影像对后续处理会产生不同程度的影响,如对地物分类精度产生影响。针对这一问题,本文分别采用不同的DSM/DEM数据(China DSM 15 m、ASTER GDEM 30 m和SRTM 90 m)对资源三号影像进行正射校正,然后对正射校正后影像利用支持向量机进行分类,比较正射校正后影像结果的分类精度。结果表明:在相同重采样方法下,影像经China DSM 15 m DSM正射校正后结果的分类精度优于ASTER GDEM 30 m DEM和SRTM 90 m DEM。