Solutions for Exterior Orientation in Photogrammetry: A Review

The determination of the attitude, the position and the intrinsic geometric characteristics of the camera is recognised as the fundamental photogrammetric problem. It can be summarised as the determination of camera interior and exterior orientation parameters, as well as the determination of 3D coordinates of object points. The term "exterior orientation"of an image refers to its position and orientation related to an exterior (object space) coordinate system. Several methods can be applied to determine the parameters of the orientation of one, two or more photos. The orientation can be processed in steps (as relative and absolute orientation) but simultaneous methods (such as bundle adjustments) are now available in many software packages. Several methods have also been developed for the orientation of single images. They are based in general on geometric and topological characteristics of imaged objects.
This paper presents a survey of classical and modern methods for the determination of the exterior parameters in photogrammetry, some of which are available as software packages (with practical examples) on the Internet. The methods presented are classified in three principal groups. In the first, a selection of approximate methods for applications that do not require great accuracy is presented. Such methods are also used to calculate values required for iterative processes. In the second group, standard point–based methods derived from collinearity, coplanarity or coangularity conditions are briefly reviewed, followed by line–based approaches. The third group represents orientation methods based on constraints and on concepts of projective geometry, which are becoming of increasing interest for photogrammetrists. In the last section, the paper gives a summary of existing strategies for automatic exterior orientation in aerial photogrammetry.     

An Approach to Single Image Automatic Orientation and Point Determination by Using Ortho-Images and a Dtm

This paper describes an approach to single image automatic orientation and point determination by using current ortho-images and a DTM, and the experience gained in its implementation. The procedure proposed automatically extracts and matches feature points in evenly distributed patches on aerial images and ortho-images. A large number of image measurements (up to several thousand) are obtained in this process and are included in a robust space resection to determine the orientation parameters of the aerial image. For point determination with a single image, a method is formalised which integrates the DTM interpolation into the space resection so that the 3D ground coordinates of the image points can be determined in a unified mathematical model. Tests and analyses of this method show that the large number of automatic image measurements relieves the requirement for complicated and precise feature extraction and matching methods. The ground points obtained from single image intersection have an accuracy of approximately 1 pixel in planimetry, which fulfils the requirement for ortho-image updating. The elevation accuracy is mainly dependent on the quality of the current DTM and the interpolation method applied to it.     

Determination of the crop row orientations from Formosat-2 multi-temporal and panchromatic images

This paper presents a technique developed for the retrieval of the orientation of crop rows, over anthropic lands dedicated to agriculture in order to further improve estimate of crop production and soil erosion management. Five crop types are considered: wheat, barley, rapeseed, sunflower, corn and hemp. The study is part of the multi-sensor crop-monitoring experiment, conducted in 2010 throughout the agricultural season (MCM’10) over an area located in southwestern France, near Toulouse. The proposed methodology is based on the use of satellite images acquired by Formosat-2, at high spatial resolution in panchromatic and multispectral modes (with spatial resolution of 2 and 8 m, respectively). Orientations are derived and evaluated for each image and for each plot, using directional spatial filters (45° and 135°) and mathematical morphology algorithms. “Single-date” and “multi-temporal” approaches are considered. The single-date analyses confirm the good performances of the proposed method, but emphasize the limitation of the approach for estimating the crop row orientation over the whole landscape with only one date. The multi-date analyses allow (1) determining the most suitable agricultural period for the detection of the row orientations, and (2) extending the estimation to the entire footprint of the study area. For the winter crops (wheat, barley and rapeseed), best results are obtained with images acquired just after harvest, when surfaces are covered by stubbles or during the period of deep tillage (0.27 > R² > 0.99 and 7.15° > RMSE > 43.02°). For the summer crops (sunflower, corn and hemp), results are strongly crop and date dependents (0 > R² > 0.96, 10.22° > RMSE > 80°), with a well-marked impact of flowering, irrigation equipment and/or maximum crop development. Last, the extent of the method to the whole studied zone allows mapping 90% of the crop row orientations (more than 45,000 ha) with an error inferior to 40°, associated to a confidence index ranging from 1 to 5 for each agricultural plot.     

Signal, orbit and attitude analysis of Japan’s first QZSS satellite Michibiki

Results are presented for Michibiki, the first satellite of Japan’s Quasi-Zenith Satellite System. Measurements for the analysis have been collected with five GNSS tracking stations in the service area of QZSS, which track five of the six signals transmitted by the satellite. The analysis discusses the carrier-to-noise density ratio as measured by the receiver for the different signals. Pseudorange noise and multipath are evaluated with dual-frequency and triple-frequency combinations. QZSS uses two separate antennas for signal transmission, which allows the determination of the yaw orientation of the spacecraft. Yaw angle estimation results for an attitude mode switch from yaw-steering to orbit-normal orientation are presented. Estimates of differential code biases between QZSS and GPS observations are shown in the analysis of the orbit determination results for Michibiki. The estimated orbits are compared with the broadcast ephemerides, and their accuracy is assessed with overlap comparisons.     

Fuzzy Logic System for Road Identification Using Ikonos Images

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     

自动空中三角测量系统开发及精度分析

在传统解析空中三角测量理论的基础上,运用数字摄影测量、数字图像处理、误差处理等理论,用VC＋＋开发自动空中三角测量程序的主要功能,并用本程序对一个实验测区进行空中三角测量处理,对实验结果做了分析,最后实践证明,利用GPS/IMU数据辅助空中三角测量,能达到较高的自动化程度。     

利用国产GF-1卫星数据实现山区细小河流河宽的自动提取

以国产GF-1卫星影像为数据源,选取皇甫川流域内山区细小河流密集的上游1421 km²作为研究区域,针对因山区河流河道狭窄、形态复杂等导致的河流边界提取难度大、精度差、河宽无法自动提取的难题,首先利用改进的变异系数法筛选水体指数,再采用改进的决策树法结合DEM河网精确获取河流边界,最后通过自动化河宽提取算法实现对山区细小河流及其河宽的自动提取。结果表明,本文方法对山区河流判别的总体精度为89.5%,有效地排除了山体阴影等地物的干扰。对河宽为0~10 m的极细河流,本文方法提取河宽的误差为18.54%;10~30 m的细小河流,提取误差为12.07%。     

遥感地面辐射观测中的视场效应问题研究

以典型的垄行作物玉米为研究对象，提出了一种新的视场效应分析方法：网格模型法。该方法将目标空间和测量空间网格化，然后在网格空间计算观测视场内的组分比例，进而确定组合信号值。本文采用网格模型法分析了垄行作物亮叶、暗叶、亮土、暗土四分量在传感器视场中面积权重变化、空隙率的变化、方向亮温的变化、红波段反射率的变化、红外波段反射率的变化以及植被指数NDVI的变化率，研究了不同观测角度情况下视场效应的变化。     

地理空间数据自动综合方法的研究现状与发展趋势

多年来人们已经报道了很多自动综合方法。这些方法确实解决了地理空间数据自动综合中的很多重要问题,但这些方法也有明显的缺陷和应用范围。本文对这些方法进行了研究,研究内容包括这些方法的分类、原理、优缺点和适用范围,并提出了今后自动综合方法的研究发展趋势。     

A hybrid measurement approach for close-range photogrammetry

Full automation in close-range photogrammetric measurement has long been a practical reality. However, constraints apply to the process such that automated 3D measurement is generally confined to targeted points in an environment of controlled illumination. The ready availability of consumer-grade digital cameras has made photogrammetric measurement accessible and more widely employed for a host of new applications, the majority of which call for 3D measurement of other than signalized object features. Process automation is therefore typically precluded. This paper discusses a hybrid measurement approach which involves fully automatic network orientation with targets, while at the same time supporting follow-up semi-automatic and manual operations such as feature point and line extraction and surface measurement via image matching. The topics discussed include camera calibration, the metric exploitation of colour attributes, issues related to image point correspondence determination, operator assisted feature measurement and surface extraction. All are important to the practical realisation of the hybrid measurement approach.     

一种聚集性面群中毗邻区自动识别与处理方法

毗邻化操作是具有毗邻特性的聚集性面状要素群(简称毗邻区)开展地图综合的核心内容,传统方法只给出了笼统的处理思路,难以支撑机器智能化、自动化处理。为此,本文提出一种在各种聚集性面状要素群中自动识别毗邻区及其毗邻化处理方法。首先基于Gestalt原则,提炼代表毗邻区典型特征的桥接面宽度指数(WI)、分布格局指数(DPI)、有效连接指数(ECI)和重叠度指数(OI),并进行毗邻区自动辨识;其次优化外围边界轮廓计算、毗邻化线提取等毗邻化操作关键算法,实现自动化处理;最后经江苏省某典型区域的地形图实际数据测试,检验了该自动化方法的可靠性和高效性。     

Measuring Earth orientation with the global positioning system

Summary A globally distributed network of high-precision receivers which obtain data from the full Global Positioning System (GPS) configuration of 18 or more satellites may soon become an efficient and economical method for the rapid determination of short-term variations in Earth orientation. A covariance analysis has been performed to evaluate the errors associated with GPS monitoring of Earth orientation. Earth orientation parameters were modeled either as constants over observing windows of various lengths, or as stochastic process-noise variables. The sensitivity of Earth orientation estimates to systematic errors in selected model parameters was also examined. GPS measurements appear to be highly competitive with those from other techniques, and have the potential to generate nearly continuous centimeter-level Earth orientation information to aid both spacecraft navigation and the study of high-frequency Earth orientation-related processes.     

Principle, software and experiment of GPS-supported aerotriangulation

1 IntroductionAs is now well known, the high accurate point de-termination with airborne remOe sensing data hasalways ben one of the most fundaxnental prObletns..in aerial photOgrammtry. According to the princi-ple of the geOmtry reversal in photOgramrntry,the interior and exterior orientation elements ofaerial phOtOgraphs must first be known in order toreconstnJct the measuring stereo geometric medels.For the past 60 years, however, the interior orienta-tion parameters of carnera were main…     

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.     

3S技术集成在土地利用更新调查中的应用

应用GPS技术对空间数据快速定位,利用RS技术提供的航片、卫星照片等影像资料,可精度较高地定位、定量到地块,直观地判读地面物体特性、资源的现势信息。把GPS、RS获取的丰富的地物信息及其他手段补充获取的各种信息提供给GIS,GIS利用空间数据库技术把属性数据的管理一体化,存储和分析处理多种性质的数据。实践证明采用3s技术进行土地利用现状更新调查,一方面可以极大提高土地利用现状更新调查的效率和质量,另一方面可以建立土地利用现状调查动态更新机制,为进行土地利用现状的日常变更和年度变更奠定基础,从而保证图、数、实地的一致,为国土资源管理提供现势性的基础资料。     

双介质摄影测量的相对定向

本文导出了双介质摄影测量的共面条件方程,它与单介质摄影测量时的共面条件方程有十分相近的形式,并推导了共面条件方程的线性化形式;针对与单个质摄影测量相对定向的区别,讨论了双个质摄影测量相对定向的计算,从而从理论上完备地解决了这一问题;最后给出模拟数据的计算结果,证实了所建立的相对定向方程和相应计算策略的正确性。     

Crack measurement: Development,testing and applications of an automatic image-based algorithm

The paper presents an Image-based Method for Crack Analysis (IMCA) which is capable of processing a sequence of digital imagery to perform a twofold task: (i) the extraction of crack borders and the evaluation of its width across the longitudinal profile; (ii) the measurement of crack deformations (width, sliding and rotation). Here both problems are solved in 2-D, but an extension to 3-D is also addressed. The equipment needed to apply the method is made up of a digital camera (or a still video-camera in case a high frequency in data acquisition is necessary), an orientation frame which establishes the object reference system, a pair of signalized supports to be placed in a permanent way on both sides of the crack to compute deformations; however, permanent targets are mandatory only for case (ii). The measurement process is carried out in a fully automatic way, a fact also that makes this technique highly operational for unskilled people in engineering surveying or photogrammetry. The accuracy of the proposed method, evaluated in experimental tests adopting different consumer digital cameras, is about ± 5–20 μm, like the accuracy of most deformometers, but with the advantage of automation and of augmented achievable information; moreover, the image sequence can be archived and off-line measurements could be performed at any time.     

Innovations in Automation for Vision Metrology Systems

The advantages of vision metrology (VM) systems over their film-based counterparts, in terms of the degree of automation within the measurement process, were initially confined to the image mensuration stage. Of late, however, the potential of significantly raising the level of automation of offline and real time VM systems has been more fully exploited, to the point where full automation of the offline procedure has been realized. Innovative features such as automatic image point identification via coded targets, exterior orientation through automatically recognizable "control" groupings of target points, determination of image point correspondences within unlabelled point clouds, and real time tracking of multipoint, handheld measurement probes are now incorporated in industrial VM systems. Another significant innovation is the development of "smart" cameras with incorporated image processing and measurement capabilities which remove the necessity for transmitting image data to the host computer. This paper reviews recent innovations in automation and discusses their operational impact on practical VM applications. The concepts discussed are illustrated through reference to a modern VM system which supports offline and real time measurement.