利用有理函数提取GeoEye-1立体像对数字高程

本文探索利用高分辨率卫星GeoEye-1卫星获取数字高程模型辅助重力改正的方法。本文介绍了有理函数模型提取立体像对中高程的技术流程,通过与地面实测控制点的对比,分析在有控制点和无控制点情况下有理函数模型提取结果的精度。研究表明有理函数模型正逐渐成为高分辨率卫星提取地形地貌的重要方法。     

IRS-P5立体像对提取DEM及精度评价

利用IRS-P5同轨立体像对构建DEM并讨论DEM的精度,分析了不同地面控制点组合下的影像定位精度。在至少采用4个地面控制点的情况下,平面和高程方向影像定位精度能够达到2 m的精度。用抽样检查和差值运算的方法对DEM的精度进行了评价,认为P5立体像对生成DEM基本满足国家1∶50 000大比例尺地形图制图的要求。实际选线证明IRS-P5影像生成的DEM满足电力选线的要求。     

基于ASTER遥感立体像对的DEM提取

卫星遥感立体像对提取DEM是地貌信息获取的一个重要里程碑,ASTER卫星传感器是可以拍摄立体像对传感器中的代表,具有数据质量稳定、覆盖广泛、价格低廉的特点。本文通过实例研究了ASTER立体像对在高山峡谷地区提取DEM的精度。首先简述ASTER的立体像对提取DEM的国内外发展现状,然后针对一处高程变化显著地区在1:10万比例尺地形图采集地面控制点(GCP),用1:5万精度的DEM作检验,获得GCP范围内高程误差为±20.4m,GCP范围外高程误差为±48.2m,平均误差是±34.3m。这证明可以在小区域内选取GCP控制点,由ASTER立体像大范围外推生成大范围DEM,而且采用常规的技术手段和普通的商业软件就可实现。该方法提取DEM对于我国地形资料缺乏的西部地区有很强的实用性。     

印度测图卫星IRS-P5定位精度初步研究

简要回顾了印度遥感卫星系列的发展历程;给出了IRS-P5卫星及传感器的有关性能参数,并与IKONOS、SPOT5 HRS做了初步比较;详细论述了IRS-P5使用有理函数模型的定位方法。最后,使用中国北京地区的立体像对数据进行了有关试验研究,结果表明,在良好的地面控制点的支持下,平面和高程精度均可达到5m,满足国家1∶50000基本比例尺地形图测图规范要求。     

基于WorldView-2制备大野口流域高分辨率DEM及精度分析

在全野外GPS地面控制点基础上,对WorldView-2影像自带RPC文件进行校正,利用数字摄影测量软件系统在立体模型上通过影像自动匹配技术快速提取黑河流域上游大野口子流域1∶5 000比例尺数字高程模型(DEM)。由于区域地形复杂、交通不便,研究区南部无地面控制点覆盖。基于立体模型交互式操作,匹配60个均匀分布高精度影像连接点,提高了DEM自动提取精度。并在对阴坡森林覆盖区、大野口水库等重点区域进行DEM编辑基础上,辅助地形特征点和线数据提高了成果精度。由15个外业控制点、12个模型保密点组成的检查点进行定量DEM验证,结果表明:两组高程中误差最大为1.9 m,达到该比例尺山地一级精度2.5 m的要求。
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资源三号卫星影像DEM提取与精度分析

为提高国产遥感卫星影像定位精度,提取高精度DEM,该文基于卫星遥感的成像模型和间接平差理论,利用有理函数模型和像面仿射变换模型,构建了卫星影像平差数学模型;利用该数学模型对资源三号卫星立体影像进行了平差处理,建立了研究区域DEM。分析结果表明:DEM在无控制点情况下,平地区域平面精度达到6.12m,高程精度达到8.39m;山地区域平面精度达到6.20m的,高程精度达到8.62m,数据精度能够满足1∶50000比例尺地形图测图标准和要求。研究结果验证了国产卫星数据的定位精度。     

地性线提高卫星林火监测几何精度的方法

利用卫星热点监测森林火灾,在我国已有近20年的应用历史,但提高火场或火点定位精度的一直没有大的突破,经过系统级及GCP控制校正的监测图像,往往还存在2~4个像元的误差,影响了开展地面核查和处置的工作效率。针对以上问题,提出了一种基于90m DEM(数字高程模型)提取地性线,并集成立体可视地形地貌图、江河及大型湖泊矢量地图,以此为地理参照数据控制校正MODIS林火监测图像的方法。实验结果表明,与原有的几何纠正技术相比,利用地性线控制精校正的监测图像,其火场的定位误差从2~4个像元提高到1个像元内,GCP(控制点)的均方误差仅为431m,该技术方法能极大地提高卫星林火监测的几何精度。     

基于区域网平差的干涉合成孔径雷达数字高程模型校正

合成孔径雷达干涉测量（InSAR）是获取数字高程模型（DEM）的常规手段,而通过干涉技术获得DEM后,其精度会受到轨道定位、影像的配准、干涉图获取、相位解缠等精度的影响。已有的利用区域网平差提升DEM精度的研究忽略了DEM的初始平面定位误差的影响。引入DEM的平面高程一体化区域网平差,将区域网平差分解为平面定位六参数的优化和高程误差模型的平差求解两个独立的平差过程,同时利用激光测高数据作为高程控制。从哨兵干涉生成的20 m分辨率DEM实验结果看,平差后DEM的高程均方根误差（RMSE）从平差前的19.372 m提升到了3.459 m。DEM对应连接点的平面内符合精度RMSE从初始182.462 m提升至14.887 m。而传统的不考虑平面误差的DEM优化方法在平差后高程精度提升至7.865 m,远低于所提出的方法,验证了提出的考虑平面误差的区域网平差方法的有效性。     

Google Earth的新卫星升天了

如果不再次出现意外的话,GeoEye公司最新的地球影像卫星GeoEye-1应该于9月4日发射升空。这颗有史以来精度最高的商用影像卫星将为GoogleEarth提供0．5m精度的卫星照片,完全可以满足某些人数下水道井盖的爱好。重1955kg的GeoEye-1在范德堡空军基地被波音公司的德尔塔Ⅱ火箭送入轨道后,     

无人飞艇低空航测系统在1:500大比例尺地形图航测中的应用

利用无人飞艇搭载组合宽角相机进行低空低速航空摄影,获取高分辨率、高清晰度、宽像幅、大航摄基高比影像,实现平面和高程测量精度的提高;采用地面标志布设像控标志点,提高坐标量测精度和空三加密精度;采用新的无人飞艇低空航测生产技术,实现满足国家规范要求的航测内业直接采集1∶500地形图平面和高程数据生产方式,解决了长期以来大比例尺航测成图内业高程测量精度达不到要求的难题,提高了航测生产效率,试验表明该技术具有较强的实用性和应用潜力。     

基于高空间分辨率与立体像对遥感数据的建筑物三维信息提取

准确获取建筑的三维分布信息对于城市规划与管理、灾害风险评估与防范以及灾后救助等都具有非常重要的意义。针对目前建筑物信息提取研究集中于二维平面信息提取,三维信息提取研究较少,且方法自动化程度较低,实用性和和推广性不足,提出了综合立体像对和高空间分辨率两种遥感数据进行建筑物三维信息提取的方法。首先,基于小波变换融合方法对GeoEye\|1高空间分辨率全色和多光谱影像进行融合,然后运用面向对象方法对融合后的高空间分辨率遥感影像进行建筑物基底轮廓提取,再利用IRS\|P5立体像对反演地物高度,最后通过数据整合获得研究区建筑物的三维空间分布。研究结果表明:该方法可以充分利用不同遥感数据的优势,获得较高的提取精度;研究所需数据容易获取,方法具有较好的可操作性和推广性。     

基于立体视觉的平面圆参数高精度测量算法*

针对目前平面圆的圆心和半径测量方法存在的不足,提出一种基于立体视觉的平面圆参数高精度测量方法。该方法首先根据边缘分组算法和二次曲线椭圆拟合判别算法提取双目图像中的椭圆特征;其次利用分段立体匹配算法获取平面圆特征上部分点的三维坐标;最后通过三维平面拟合、坐标转换、平面圆拟合以及坐标反变换获取平面圆的圆心和半径参数。实验结果表明,该方法有效地减小了平面圆透视投影引起的畸变误差,提高了平面圆参数的测量精度。     

不同模式Radarsat 影像DEM 提取及精度比较

利用摄影测量方法进行DEM 提取是热带雨林地区雷达应用方向之一。以热带雨林地区平地、丘陵和山地混合地形区为研究对象, 收集了F、S 和W 等不同波束模式的Radarsat-1 SAR 影像9 景, 组合成6 个不同类型的立体像对, 进行DEM 提取, 探讨基于距离ö多普勒构像方程的Radarsat 影像的DEM 提取方法。通过对DEM 结果进行精度验证和比较, 认为提取的DEM 精度受多种因素影响, 同种波束模式的立体配置, 立体交会角越大,DEM 精度越高; 对于地表起伏较小的平地,DEM 精度要高于丘陵山地区, 该研究区DEM 精度的平均误差可以达到14 m 左右,RMSE 可以达到29 m 左右。     

DSM generation and evaluation from QuickBird stereo imagery with 3D physical modelling

A digital terrain model (DTM) extracted from QuickBird in-track stereo images using a three-dimensional (3D) multisensor physical model developed at the Canada Centre for Remote Sensing, Natural Resources Canada was evaluated. Firstly, the stereo photogrammetric bundle adjustment was set-up with about 10 accurate ground control points and 1-2 m errors in the three axes were obtained over 48 independent checkpoints. The DTM was then generated using an area-based multi-scale image matching method and 3D semi-automatic editing tools and then compared to lidar elevation data with 0.2-m accuracy. An elevation error with 68% confidence level (LE68) of 6.4 m was achieved over the full area. Since the DTM is in fact a digital surface model where the height, or a part, of land cover (trees, houses) is included, the accuracy depends on the land cover types. Using 3D visual classification of the stereo QuickBird images, different classes (deciduous, conifer, mixed and sparse forests, residential areas, bare soils and lakes) were generated to take into account the height of the surfaces (natural and human-made) in the accuracy evaluation. LE68 values of 3.4 m to 6.7 m were thus obtained depending on the land cover types with biases representative of the surface heights. On the other hand, LE68 values of 0.5 m and 1.3 m with no bias were obtained for lakes and bare soils respectively. These last results are more representative of the real stereo QuickBird potential for DTM and 5-m contour line generation, compliant with the highest topographic standard. Since the images were acquired in wintertime and the lidar data in summertime, better results could thus be expected when using stereo images acquired in summertime, mainly in deciduous forests to integrate the full canopy height into the DSM.     

立体视觉中的双目匹配方法研究

本文首先对已有的双目立体视觉方法进行分析和总结 ,并依所选取的匹配特征和匹配方法的不同而将其分为利用灰度图像区域间相似性、特征点相关、边界或二阶导数过零点、二值拉普拉斯图像匹配、校正透视形变、动态规划、利用区域分割的结果和立体视觉连续性原理的各种演绎等类 ;然后对用金字塔图匹配边界基元的双目立体视觉方法进行了重点探讨 ;本文还对利用基极线约束实现匹配进行详细分析与推导     

GeoEye-1 and WorldView-2 pan-sharpened imagery for object-based classification in urban environments

The latest breed of very high resolution (VHR) commercial satellites opens new possibilities for cartographic and remote-sensing applications. In fact, one of the most common applications of remote-sensing images is the extraction of land-cover information for digital image base maps by means of classification techniques. The aim of the study was to compare the potential classification accuracy provided by pan-sharpened orthoimages from both GeoEye-1 and WorldView-2 (WV2) VHR satellites over urban environments. The influence on the supervised classification accuracy was evaluated by means of an object-based statistical analysis regarding three main factors: (i) sensor used; (ii) sets of image object (IO) features used for classification considering spectral, geometry, texture, and elevation features; and (iii) size of training samples to feed the classifier (nearest neighbour (NN)). The new spectral bands of WV2 (Coastal, Yellow, Red Edge, and Near Infrared-2) did not improve the benchmark established from GeoEye-1. The best overall accuracy for GeoEye-1 (close to 89%) was attained by using together spectral and elevation features, whereas the highest overall accuracy for WV2 (83%) was achieved by adding textural features to the previous ones. In the case of buildings classification, the normalized digital surface model computed from light detection and ranging data was the most valuable feature, achieving producer's and user's accuracies close to 95% and 91% for GeoEye-1 and VW2, respectively. Last but not least and regarding the size of the training samples, the rule of ‘the larger the better' was true but, based on statistical analysis, the ideal choice would be variable depending on both each satellite and target class. In short, 20 training IOs per class would be enough if the NN classifier was applied on pan-sharpened orthoimages from both GeoEye-1 and WV2.     

2D/3D information fusion for building extraction from high-resolution satellite stereo images using kernel graph cuts

This study presents a building extraction strategy from High-resolution satellite stereo images (HRSSI) using 2D and 3D information fusion. In the 2D processing strategy, a visible vegetation index (VVI) is generated. In the 3D processing, a disparity map is generated using semi-global matching (SGM). To remove defects from the disparity map, an object-based approach is proposed by using mean-shift image segmentation and extracting rectangles. By removing terrain effects, a normalized disparity map (nDM) is produced. In the next step, vegetation pixels are removed from nDM and an initial building mask is generated. As nDM does not have precise building boundaries, hybrid segmentation by the kernel graph cut (KGC) is applied to the feature space including the RGB, nDM, and VVI and the results are used in a decision level fusion step. By this methodology, segments that are highly intersected with initial building mask are classified as buildings. Finally, a building boundary refinement (BBR) algorithm is applied to buildings for removing the remaining defects. The proposed method is applied to two pairs of GeoEye-1 stereo images including residential and industrial test areas. Evaluation results show the completeness and correctness level of higher than 90% for the two test areas. Further evaluations show that the quality metric has significantly changed after decision level fusion using the KGC.     

基于立体视觉的高精度标定与测量方法

立体视觉测量系统中,光学系统产生的畸变使目标的成像偏离了理论成像点,导致系统产生测量误差。针对提高系统测量精度的问题,提出一种基于立体视觉的测量方法。首先,根据标定板上各角点的像素分辨率,拟合整个成像平面的四次多项式,且多项式的系数与物体到相机的距离成比例;然后,应用双目测距原理,测量被测物体的纵向距离;最后,基于所得的多项式,应用单目相机测量待测物体的横向尺寸。实验结果表明,对于所提方法,当物体距离相机5 m以内时,其纵向距离误差可以减小到5%以内;当物体距离相机1 m时,其横向宽度测量误差在0.5 mm内,逼近理论最高分辨率。     

面向物流分拣的多立体摄像头物体操作系统

为满足物流分拣的低成本和实时性要求,提出了基于多个立体摄像头的系统获取典型物体的完整立体信息的方法,并结合机械臂搭建了实验硬件平台。实验采用了2个微软Kinect摄像头在水平面上实现了约3 mm精度的物体定位,根据物体的立体信息建立立体模型,并计算了物体的取向、尺寸、含有的平面等多个可用于物体操作的立体特征,计算速率约为1 s/帧。根据这些信息,使用了机械臂成功进行了连续100次抓取。实验结果表明,这套方法和平台无需离线学习即可以实时提取多种尺寸和形状的物体的立体特征,机械臂可以基于此进行精度较高的物体操作。     

A drainage system analysis evaluation of,and comparison between,Landsat-3 RBV,Landsat-5 TM and SPOT PA imageries covering the Central Macedonia district,Greece

Abstract

Landsat-3 RBV, Landsat-5 TM imageries and SPOT PA stereopair diapositives were visually interpreted for the purpose of finding the accuracy of certain morphometric variables of three drainage basin sample areas in Central Macedonia, North Greece, drawn separately from each of the above three types of satellite imageries and comparisons were made between the efficiency of drainage systems drawn from each of the above imageries and the drainage systems extracted from the available topographic maps of 1:50000 scale.

The main findings were the following: (1) SPOT PA stereopair diapositives of 1:200000 scale can be used to map drainage systems to an order of magnitude slightly more than TM imagery of 1:125000 scale, but significantly more than RBV imagery of 1:125000 scale. This slight superiority of SPOT imagery over TM imagery implies that the greater spectral range of TM, compared with the shorter range of SPOT imageries, vastly outweighs the advantage of SPOT'S superior resolution, but not the superiority of stereoscopic view; (2) TM imagery can be used to map drainage systems to an order of magnitude significantly more than RBV imagery; and (3) RBV imagery can be used to map drainage systems to an order of magnitude less than topographic maps of 1:50000 scale but better than topographic maps of 1:100000 scale.