矢量与遥感影像的自动配准
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摘要
摄影测量与遥感技术的快速发展使得实时、全天候、大面积获取地表信息的高精度、高分辨率、多时相、多光谱的数字影像成为现实,但与之相反的却是图像处理的理论和技术手段的严重滞后,大量堆积如山的遥感影像及相关的数据处理手段之间,存在巨大的反差。摄影测量与遥感研究的重点是从数字影像自动提取所摄对象的空间和属性信息,是地理信息系统的重要数据来源,地理数据的快速获取与更新已成为困扰摄影测量、遥感、地理信息系统等领域的一个难题。许多国家目前己完成覆盖全国的基本比例尺地形图的测图计划,但由于经济的迅速发展和自然因素的影响,地表在不断发生变化,因而地图修测成为当前的主要任务。遥感影像(包括航空影像和卫星影像,特别是高分辨率的卫星影像)是目前地图更新的主要也是最有效的数据源,遥感影像和地图的精确配准是地图更新的首要步骤,所谓配准就是求解影像的外参数(外方位元素),对其进行纠正和地理编码,建立和要更新数据的对应关系,其配准精度决定了更新的精度。由于地图和影像上同名地物表示的方式差异较大,到目前为止对应的控制点仍然需要人工量测。无论在野外还是在室内地形图上量测控制点都是一件耗时、耗人力物力的繁冗工作,而且不容易准确量测,这越来越成为地图修测和海量遥感数据几何处理中全自动空中三角测量的瓶颈。在包括中国在内的许多国家基本比例尺的地形图和正射影像测制任务已基本完成,如何利用已有的信息,作为先验知识和初值辅助影像上地物提取以及作为控制信息对新影像进行外参数求解,已经成为当前摄影测量自动化的一个重要研究方向,为解决遥感数据处理的“瓶颈”问题提供了一个新的思路。
本文的研究目标是利用已有的地图信息,通过遥感影像相应地物的自动提取,自动生成大量的控制信息。通过扩展直线摄影测量原理和算法,计算出遥感影像的外参数(外方位元素),实现新影像和旧矢量地图的自动配准。对于整个测区的影像而言,研究利用不同几何特征的控制信息的混合光束法区域网平差和粗差剔除方法,实现测区影像和地图间的整体配准,为地形图快速修测奠定基础。主要内容包括以下几点:
系统地回顾了矢量与遥感影像配准以及遥感影像自动外参数计算的研究现状,分析了各自的优点和不足之处,讨论了该方向的研究趋势,并对空间数据之间的配准进行了定义。通过分析线状特征相对于点状特征的优点,充分利用已有地图中大量的线状控制信息,提出并实现了矢量与遥感影像自动配准以及遥感影像自动外参数解算的策略和系统。
自动计算遥感影像的外参数是以遥感影像的成像几何关系为基础的,本文讨论了目前比较常用的光学遥感影像的成像几何关系,并列出其相应的数学表达形式。对每类影像从严格光束几何模型进行讨论其成像几何关系,另外对卫星影像分析了传统的共线方程表达形式在计算过程中的缺点,选用当前最新的研究成果,克服了参数相关性这一难题。
量测大量的控制信息是实现矢量地图和遥感影像的配准以及计算遥感影像的外参数的基础,控制线相对于控制点在自动化和可靠性方面具有明显的优势。本文综合利用目前遥感影像线状地物自动提取和半自动提取的各自优点,结合本文所研究的遥感影像的特点,详细阐述了以Snake为主的能量最小化方法在线状地物自动提取中的应用和基于最小二乘模板匹配的精确定位方法,分别讨论不同分辨率影像上的线状地物自动提取方法和策略。根据线状地物的特征,对阶跃型边缘特征的基于最小二乘模板匹配提取算法进行扩展,通过在最小二乘匹配中引入“比例尺”变化参数,提出一种不严格等宽平行线(中心线)精确定位方法。影像上提取的线状特征和对应的已有矢量数据中的线状地物共同组成控制线,为矢量和影像的自动配准以及影像外参数自动计算提供观测值。
The rapid progress of photogrammetry and remote sensing makes digital image acquisition of high resolution, accuracy, multi-temporal resolution, multi-spectrum and real time images coming to truth, but the corresponding theory and methodology of processing can not catch up with the rapid development of data acquisition. There is a sharp contrast between mass of remote sensing imagery and the theory and methodology of data processing. The automatic acquisition of the spatial and attributive information of the ground object from remote sensing images is one of the important research areas in photogrammetry and remote sensing, which is also main data source to geography information system (GIS). Quickly collecting and automatically updating geographic data have become a difficult task in the areas of photogrammetry, remote sensing and GIS. At present, many countries have accomplished the schedule of topographical mapping around the countries with the basic scale. The need of making map revision arises due to the addition or removal of terrain features. The rapid changes in the map contents and the need for up-to-date maps have compelled surveyors to focus their attention to the development of faster and more economical map revision processes. Photogrammetric techniques and satellite techniques are main means for the map revision, in which remote sensing imagery are effective and economical data source, especially for high-resolution satellite image. In the processing the captured image, the first step is calculating the parameters of image position and orientation, based that the image is registered to the map. The precision of map revision is determined by the precision of the geographic registration. Up to now the conjugate points are measured manually for registration between the map and the image because of the difference between the images and corresponding maps. The manual measure of the conjugate points is a time-consuming and tedious task and the precision of the conjugate points is low. This has become a bottle-neck to map revision and the automatic Aero-triangulation in the geometrical process of mass remote sensing images. How to use the exiting map and ortho-image as knowledge and initial position to automatically extract the linear primitives from remote sensing images, which can be used as control information for image orientation and registration, has become a new way to photogrammetric automation. This is a new idea for solving the bottle-neck problem of remote sensing images processing.In this dissertation, many conjugate lines are automatically generated by automatic extraction of linear primitives from new remote sensing images based exiting vector maps. The exterior orientation parameters of the images are calculated based on the theory and the arithmetic of the extended line photogrammetry, in which the conjugate lines are used as the observational values. For many overlapping images in a block, the images are registered to the corresponding maps by the hybrid bundle block adjustment based on multi-conjugate primitives with different geometric characteristic. This lays a foundation for map revision by automatically registering the new image to the exiting map. Main content of the dissertation are discussed as following.This dissertation summarizes the exiting methods and arithmetic about the registering remote sensing images with vector map and the automatic orientation of the images in the literatures. The pro and con of the methods and arithmetic are analyzed and the research trend is discussed in the field. In this dissertation the registration between spacial data is defined. The software and the strategy proposed in this dissertation can realize the registration between the remote sensing images and the vector map by maidng fully use of many linear conjugate lines with the analyzing the line primitive's advantage over point one.
Automatic calculating the exterior orientation parameters of remote sensing images is based on building the imaging projective geometry. The imaging projective geometry of common optical remote sensing images and their conditional equations are outlined in this dissertation. For satellite images, the disadvantage of the traditional collinear conditional equations is analyzed and the new strict geometric model is adopted from the literatures. So the problem of the relativity of image parameters calculation is solved completely.Automatic extracting many conjugate lines, which have obvious advantage over the conjugate points in automation and reliability, is the base of registering image to map and calculating of image's exterior orientation parameters. The method of linear primitives extraction mainly based on active contour model is dwelled on according to the image characteristics by combining the advantage of automatic extraction and semi-automatic extraction of linear primitives at present. So do the precisely locating of linear primitives based on the extended least squares template matching (LSTM). Different strategies and methods of extraction are adopted based on the image spatial resolution. The self-adaptive LSTM is extended for the extraction of edges with non-equal width and centerline of ribbon primitives by introducing a "scale" parameter in the LSTM. The extracted linear primitives are used as conjugate lines with the corresponding linear primitives on vector map, which are used as observational values for the adjustment in the image exterior orientation and the registration.Line photogrammetry, which has better automation and high reliability, is new research field with the aim to accomplishing a series of photogrammetric tasks by using linear primitives, such as relative orientation, spatial resection, spatial intersection and block aero-triangulation. With the progress of the satellite remote sensing technology, more and more high-resolution remote sensing images can be afforded. Most remote sensing images are captured by linear array scanner with charged coupled device (CCD) because of the technology of sensor and economical fact, in which every image line has individual exterior orientation parameters. The points on the linear primitive in the image have different exterior orientation parameters although every point is captured on the condition of perspective geometry. So the coplanar condition equation in the line photogrammetry for frame image cannot apply to the image captured by the linear array scanner. To circumvent this problem, the coplanar condition equation should be extended. In mathematics, all lines and curves consist of points. Same as visual point, co-linear equation can be used to the points in line feature, and all feature points can come down to the points in order to fit the co-linear equation, that is so called as generalized point photogrammetry. Consequently, it is easy to reduce the points, lines and curves into one mathematical model, which can apply to all kinds of remote sensing images. On the otherwise, the corresponding conclusions about the collinear condition equation can keep on adopting.To assess effectiveness the proposed arithmetic in generalized point photogrammetry, one is always required to understand its sensitivity and robustness, i.e., how perturbations in input data affect the output result. Through a series of test, this dissertation analyzes the elimination of blunders, and the effect of the precision and convergence speed of adjustment produced by the distributing and error of the conjugate lines. The redundancy and relativity of the observation are analyzed, so do the stability of the adjustment. The conclusion is drawn that to accomplish the spatial resection in generalized point photogrammetry, three unparallel conjugate lines each other are at least needed. The software system built for test the proposed arithmetic can realize the task of automatic single image (model) registering to vector map. The addition of conjugate lines makes the registration better and more rational at the distributing area of many linear primitives. The changed linear primitives such
as roads and rives can be check out on the based of the results of extraction and the adjustment, which can be also used for map revision.For many overlapping images in a block, the images are registered to the corresponding maps by the hybrid bundle block adjustment of generalized point photogrammetry based on multi-conjugate primitives with different geometric characteristics. In the block adjustment, the extended collinear equation is used as the conditional equation and the strategy of line translation is proposed for tie lines or pass lines. All images' exterior orientation parameters are calculated on the restriction of minimizing the error of all observations, which realize the whole registration between the images and corresponding maps. The block adjustment not only can circumvent the problem of the deficiency in conjugate lines such as the block water area, but also eliminates system error between the adjacent images at best, which can improve the precision of the registration between images and corresponding maps and the mosaic between the adjacent images.By the strategies and arithmetic mentioned above, some experiments are carried on for a lot of images including aerial images, SPOT and Landsat TM images with different resolutions. All of the results are quite perfect by analyzing the precision. The conclusion can be drawn that the automatic registration can be realized between remote sensing images and corresponding vector maps by addition of conjugate lines in generalized point photogrammetry. The precision can meet the need of the map revision with corresponding scale, which has the relationship with images' scale and the precision of vector maps and digital elevation model (DEM).With the pressing need for map revision, it is more and more important to do research in the field of automatic exterior orientation for remote sensing images, which can be used for rectifying the images and registering the images to the corresponding vector maps. The operational strategy and research content in this dissertation might be a help to the automation in photogrammetry and remote sensing at a certain extent.
本文的研究目标是利用已有的地图信息,通过遥感影像相应地物的自动提取,自动生成大量的控制信息。通过扩展直线摄影测量原理和算法,计算出遥感影像的外参数(外方位元素),实现新影像和旧矢量地图的自动配准。对于整个测区的影像而言,研究利用不同几何特征的控制信息的混合光束法区域网平差和粗差剔除方法,实现测区影像和地图间的整体配准,为地形图快速修测奠定基础。主要内容包括以下几点:
系统地回顾了矢量与遥感影像配准以及遥感影像自动外参数计算的研究现状,分析了各自的优点和不足之处,讨论了该方向的研究趋势,并对空间数据之间的配准进行了定义。通过分析线状特征相对于点状特征的优点,充分利用已有地图中大量的线状控制信息,提出并实现了矢量与遥感影像自动配准以及遥感影像自动外参数解算的策略和系统。
自动计算遥感影像的外参数是以遥感影像的成像几何关系为基础的,本文讨论了目前比较常用的光学遥感影像的成像几何关系,并列出其相应的数学表达形式。对每类影像从严格光束几何模型进行讨论其成像几何关系,另外对卫星影像分析了传统的共线方程表达形式在计算过程中的缺点,选用当前最新的研究成果,克服了参数相关性这一难题。
量测大量的控制信息是实现矢量地图和遥感影像的配准以及计算遥感影像的外参数的基础,控制线相对于控制点在自动化和可靠性方面具有明显的优势。本文综合利用目前遥感影像线状地物自动提取和半自动提取的各自优点,结合本文所研究的遥感影像的特点,详细阐述了以Snake为主的能量最小化方法在线状地物自动提取中的应用和基于最小二乘模板匹配的精确定位方法,分别讨论不同分辨率影像上的线状地物自动提取方法和策略。根据线状地物的特征,对阶跃型边缘特征的基于最小二乘模板匹配提取算法进行扩展,通过在最小二乘匹配中引入“比例尺”变化参数,提出一种不严格等宽平行线(中心线)精确定位方法。影像上提取的线状特征和对应的已有矢量数据中的线状地物共同组成控制线,为矢量和影像的自动配准以及影像外参数自动计算提供观测值。
The rapid progress of photogrammetry and remote sensing makes digital image acquisition of high resolution, accuracy, multi-temporal resolution, multi-spectrum and real time images coming to truth, but the corresponding theory and methodology of processing can not catch up with the rapid development of data acquisition. There is a sharp contrast between mass of remote sensing imagery and the theory and methodology of data processing. The automatic acquisition of the spatial and attributive information of the ground object from remote sensing images is one of the important research areas in photogrammetry and remote sensing, which is also main data source to geography information system (GIS). Quickly collecting and automatically updating geographic data have become a difficult task in the areas of photogrammetry, remote sensing and GIS. At present, many countries have accomplished the schedule of topographical mapping around the countries with the basic scale. The need of making map revision arises due to the addition or removal of terrain features. The rapid changes in the map contents and the need for up-to-date maps have compelled surveyors to focus their attention to the development of faster and more economical map revision processes. Photogrammetric techniques and satellite techniques are main means for the map revision, in which remote sensing imagery are effective and economical data source, especially for high-resolution satellite image. In the processing the captured image, the first step is calculating the parameters of image position and orientation, based that the image is registered to the map. The precision of map revision is determined by the precision of the geographic registration. Up to now the conjugate points are measured manually for registration between the map and the image because of the difference between the images and corresponding maps. The manual measure of the conjugate points is a time-consuming and tedious task and the precision of the conjugate points is low. This has become a bottle-neck to map revision and the automatic Aero-triangulation in the geometrical process of mass remote sensing images. How to use the exiting map and ortho-image as knowledge and initial position to automatically extract the linear primitives from remote sensing images, which can be used as control information for image orientation and registration, has become a new way to photogrammetric automation. This is a new idea for solving the bottle-neck problem of remote sensing images processing.In this dissertation, many conjugate lines are automatically generated by automatic extraction of linear primitives from new remote sensing images based exiting vector maps. The exterior orientation parameters of the images are calculated based on the theory and the arithmetic of the extended line photogrammetry, in which the conjugate lines are used as the observational values. For many overlapping images in a block, the images are registered to the corresponding maps by the hybrid bundle block adjustment based on multi-conjugate primitives with different geometric characteristic. This lays a foundation for map revision by automatically registering the new image to the exiting map. Main content of the dissertation are discussed as following.This dissertation summarizes the exiting methods and arithmetic about the registering remote sensing images with vector map and the automatic orientation of the images in the literatures. The pro and con of the methods and arithmetic are analyzed and the research trend is discussed in the field. In this dissertation the registration between spacial data is defined. The software and the strategy proposed in this dissertation can realize the registration between the remote sensing images and the vector map by maidng fully use of many linear conjugate lines with the analyzing the line primitive's advantage over point one.
Automatic calculating the exterior orientation parameters of remote sensing images is based on building the imaging projective geometry. The imaging projective geometry of common optical remote sensing images and their conditional equations are outlined in this dissertation. For satellite images, the disadvantage of the traditional collinear conditional equations is analyzed and the new strict geometric model is adopted from the literatures. So the problem of the relativity of image parameters calculation is solved completely.Automatic extracting many conjugate lines, which have obvious advantage over the conjugate points in automation and reliability, is the base of registering image to map and calculating of image's exterior orientation parameters. The method of linear primitives extraction mainly based on active contour model is dwelled on according to the image characteristics by combining the advantage of automatic extraction and semi-automatic extraction of linear primitives at present. So do the precisely locating of linear primitives based on the extended least squares template matching (LSTM). Different strategies and methods of extraction are adopted based on the image spatial resolution. The self-adaptive LSTM is extended for the extraction of edges with non-equal width and centerline of ribbon primitives by introducing a "scale" parameter in the LSTM. The extracted linear primitives are used as conjugate lines with the corresponding linear primitives on vector map, which are used as observational values for the adjustment in the image exterior orientation and the registration.Line photogrammetry, which has better automation and high reliability, is new research field with the aim to accomplishing a series of photogrammetric tasks by using linear primitives, such as relative orientation, spatial resection, spatial intersection and block aero-triangulation. With the progress of the satellite remote sensing technology, more and more high-resolution remote sensing images can be afforded. Most remote sensing images are captured by linear array scanner with charged coupled device (CCD) because of the technology of sensor and economical fact, in which every image line has individual exterior orientation parameters. The points on the linear primitive in the image have different exterior orientation parameters although every point is captured on the condition of perspective geometry. So the coplanar condition equation in the line photogrammetry for frame image cannot apply to the image captured by the linear array scanner. To circumvent this problem, the coplanar condition equation should be extended. In mathematics, all lines and curves consist of points. Same as visual point, co-linear equation can be used to the points in line feature, and all feature points can come down to the points in order to fit the co-linear equation, that is so called as generalized point photogrammetry. Consequently, it is easy to reduce the points, lines and curves into one mathematical model, which can apply to all kinds of remote sensing images. On the otherwise, the corresponding conclusions about the collinear condition equation can keep on adopting.To assess effectiveness the proposed arithmetic in generalized point photogrammetry, one is always required to understand its sensitivity and robustness, i.e., how perturbations in input data affect the output result. Through a series of test, this dissertation analyzes the elimination of blunders, and the effect of the precision and convergence speed of adjustment produced by the distributing and error of the conjugate lines. The redundancy and relativity of the observation are analyzed, so do the stability of the adjustment. The conclusion is drawn that to accomplish the spatial resection in generalized point photogrammetry, three unparallel conjugate lines each other are at least needed. The software system built for test the proposed arithmetic can realize the task of automatic single image (model) registering to vector map. The addition of conjugate lines makes the registration better and more rational at the distributing area of many linear primitives. The changed linear primitives such
as roads and rives can be check out on the based of the results of extraction and the adjustment, which can be also used for map revision.For many overlapping images in a block, the images are registered to the corresponding maps by the hybrid bundle block adjustment of generalized point photogrammetry based on multi-conjugate primitives with different geometric characteristics. In the block adjustment, the extended collinear equation is used as the conditional equation and the strategy of line translation is proposed for tie lines or pass lines. All images' exterior orientation parameters are calculated on the restriction of minimizing the error of all observations, which realize the whole registration between the images and corresponding maps. The block adjustment not only can circumvent the problem of the deficiency in conjugate lines such as the block water area, but also eliminates system error between the adjacent images at best, which can improve the precision of the registration between images and corresponding maps and the mosaic between the adjacent images.By the strategies and arithmetic mentioned above, some experiments are carried on for a lot of images including aerial images, SPOT and Landsat TM images with different resolutions. All of the results are quite perfect by analyzing the precision. The conclusion can be drawn that the automatic registration can be realized between remote sensing images and corresponding vector maps by addition of conjugate lines in generalized point photogrammetry. The precision can meet the need of the map revision with corresponding scale, which has the relationship with images' scale and the precision of vector maps and digital elevation model (DEM).With the pressing need for map revision, it is more and more important to do research in the field of automatic exterior orientation for remote sensing images, which can be used for rectifying the images and registering the images to the corresponding vector maps. The operational strategy and research content in this dissertation might be a help to the automation in photogrammetry and remote sensing at a certain extent.
引文
1 张祖勋,张剑清.数字摄影测量学.1996,武汉:武汉测绘科技大学出版社.
2 李德仁,郑肇葆.解析摄影测量学.1992,北京:测绘出版社,pp.4-5.
3 张祖勋,张剑清.数字摄影测量学的发展和应用.测绘通报,1996(6):pp.12-17
4 李德仁.摄影测量与遥感的现状及发展趋势.武汉测绘科技大学学报,2000,25(1):pp.1-5
5 张祖勋,张剑清,张力.数字摄影测量学发展的机遇与挑战.武汉测绘科技大学学报,2000,25(1):pp.7-11.
6 李德仁等.摄影测量与遥感概论.2001,北京:测绘出版社.
7 Peter P. Product survey on digital photogrammetry workstation. GIM international, 2001(4): pp. 69-73.
8 Konecny G. Future prospects of mapping from space. Proceeding of SIST' 98. Wuhan: WTUSM, 1998: PP. 143-159.
9 李德仁,周月琴.空间测图——现状与未来.测绘通报,2000(1):pp.3-7.
10 粱家琳.地物要素变化探测与地图更新自动化方法.测绘科技通讯,1997(4):pp.15-17
11 蒋捷,陈军.基础地理信息数据库更新的若干思考.测绘通报,2000(5).
12 I. J. DOWAN. Automating image registration and absolute orientation: solutions and problems. Photogrammetric Record, 16(91)(April 1998): pp. 5-18.
13 Lisa Gottesfeld Brown. A Survey of Image Registration Technology. Report of Department of Computer Science Columbia University New York, January 12, 1992.
14 Hui Li, B.s. Manjunath, Sanjit K. Mitra. A Contour-Based Approach to Multisensor Image Registration. IEEE Transactions On Image Process, March 1995, 4(3): pp320-334.
15 Xiaolong Dai, Siamak Khorram. A Feature-Based Image Registration Algorithm Using Improved Chain-Code Representation Combined with Invariant Moments. IEEE Transactions On Geoscience and Remote Sensing, September 1999,37(5),pp. 2351-2362.
16 C. Drewniok, K. Rohr. Automatic Exterior Orientation of Aerial Images in Urban Environments. International Archives of Photogrammetry and Remote Sensing, 1996, Vol. ⅩⅩⅩⅠ part B3 pp. 146-152.
17 Stefan Growe, Ralf Tonjes. A Knowledge Based Approach to Automatic Image Registraction. International Conference on Image Processing(ICIP'97),scheduled for October 26-29,1997 in Santa Barbara, CA, USA, IEEE Published
18 JUrgen BUckner. Model Based Road Extraction For The Registration And Interpretation Of Remote Sensing Data. ISPRS Commission IV Symposium on' GIS-Between Visions and Applications, Stuttgart, Germany, 7.9.-10.9.98.
19 F. A. van den Heuvel. Exterior Orientation using Coplanar Parallel Lines. Proceedings of the 10th Scandinavian Conference on Image Analysis, Lappeenranta, ISBN 951-764-145-1, 1997: pp. 71-78.
20 F.A. van den Heuvel. ALine-photogrammetric mathematical model for the reconstruction of polyhedral objects, in Videometrics VI, Sabry F. EI-Hakim (ed.), Proceedings of SPIE Vol. 3611, ISBN 0-8194-3112-5,1999: pp. 60-71.
21 Ian Dowman. Automated Procedures For Integration Of Satellite Images And Map Data For Change Detection: The Archangel Project IAPRS. Vol. 32,Part 4"GIS-Between Visions and Applications', Stuttgart, 1998: pp. 162-169.
22 M.J. SMITH, D.W.G. PARK. Towards A New Approach.For Absolute And Exterior Orientation. Photogrammetric Record, 16(94) (October 1999): pp. 617-623
23 Qiang Ji. A robust linear least-squares estimation of camera exterior orientation using multiple geometric features. ISPRS Journal of Photogrammetry & Remote Sensing, 2000(55) : pp. 75-93.
24 Heiner HILD, Norbert HAALA, Dieter FRITSCH. A Strategy For Automatic Image To Map Registration. IAPRS, Vol. XXXIII, Amsterdam, 2000 (Institute for Photogrammetry (ifp), Stuttgart University, Germany
25 Elli Petsa, George E. Karras. Constrained Line-Photogrammetric 3d Reconstruction From Stereopairs. IAPRS, Vol.XXXIII, Amsterdam, 2000 (Institute for Photogrammetry (ifp), Stuttgart University, Germany
26 Taravudh Tipdecho. Automatic Image Registration between Image and Object Spaces. Proceedings of the Open source GIS-GRASS users conference 2002, Trento, Italy, September 2002: pp. 11-13.
27 Ayman Habib, Michel Morgan, Young-Ran Lee. Bundle Adjustment With Selfcalibration Using Straight Lines. Photogrammetric Record, October, 2002.
28 Joachim Hohle. Automated Orientation of Aerial Images. I: Bildteknik, Image Science, 2002, Nr. 1. s. pp. 91-101.
29 Habib, A. F., Kelley, D., Asmamaw, A., New approach to solving matching problems in photogrammetry. International Archives of Photogrammetry and Remote Sensing, Amsterdam, the Netherlands, 2000, 33(B2): pp. 257-264.
30 Habib, A. F., Kelley D., Single photo resection using the modified Hough transform. Journal of Photogrammetric Engineering & Remote Sensing, 2001, 67(8): pp909-914.
31 Habib, A. F. and Kelley, D., Automatic relative orientation of large scale imagery over urban areas using modified iterated Hough transform. International Journal of Photogrammetry & Remote Sensing, 2001,56(2001): pp.29-41.
32 HsiangTseng Lin. Autonomous Recovery of Exterior Orientation of Imagery using Free-Form Linear Feature. Ph. D Dissertation of Ohio State University, UMI Number:3049072, 2002.
33 Garry H. Zalmanson. Hierarchical recovery of exterior orientation from parametric and natural 3-D curves. Ph. D Dissertation of Ohio State University, UMI Number:9962467, 2000.
34 Young-ran Lee. Pose estimation of line cameras using linear features. Ph. D Dissertation of Ohio State University, UMI Number:3049066, 2002.
35 Gulch, E. Using Feature Extraction to Prepare the Automated Measurement of Control Points in Digital Aerial Triangulation. ISPRS Comm. III Symposium, Munich, IAP 1994, Vol. 30-3/1.
36 Gulch, E. Automatic Control Point Measurement. In: Photogrammetric Week ' 95, Fritsch, D., Hobbie, D. (Eds.),Wichmann Verlag, Heidelberg, 1995: pp. 185-196.
37 Drewniok, C., Rohr, K., Automatic Exterior Orientation of Aerial Images in Urban Environments. In: International Archives of Photogrammetry and Remote Sensing, 1992, vol. 31,B3,pp. 146-152.
38 Hahn, M., Kiefner, M., Quednau, A., Hinz, E., Semi-Automatic Measurement of Signalized Ground Control Points at Digital Photogrammetric Workstations. In: International Archives of Photogrammetry and Remote Sensing, 1996, vol. 31, 83, pp. 291-296.
39 Schickler W., Feature Matching for Outer Orientation of Single Images Using 3-D Wireframe Control Points. In: International Archives of Photogrammetry and Remote Sensing, 1992, vol. 29,83.
40 Vosselman, G. and Haala, N., Erkennung topographischer Pabpunkte durch relationale Zuordnung. ZPF 6/92,1992.
41 Halla, N., Vosselman, G., Recognition of road and river patterns by relational matching. Ibid., 1992,29(83): pp. 969-975.
42 Orgado, A., Do,an, I., A procedure for automatic absolute orientation using aerial photographs and a map. ISPRS Journal of Photogrammetry & Remote Sensing, 1997, 52(4): pp. 169-182.
43 Ayman Habib, Andinet Asmamaw, Devin Kelley, Mania May. Linear Features in Fhotogrammetry. Report in Feodetic Science and Surveying, Department of Civil and Enviriamental Engineering and Geodetic Science, The Ohio State University, January 2000, No. 450.
44 Heipke, C., Automation of interior, relative, and absolute orientation. ISPRS Journal of Photogr~metry & Remote Sensing, 1997, 52(1): pp. 1-19.
45 Heikkinen, J., Laiho, A. The use of linear features as reference datum in digital map revision. ISPRS, Washington D.C., U.S.A., 1992, Vol. ⅩⅩⅠⅩ, Part 84, pp. 500-506.
46 Ackermann, F. Geo-Kodierung ohne PaBpunkte. In: Geo-Informations-Systeme, 1997, 10(2): pp. 28-32.
47 Fritsch, D., M. Cramer, M. Englich, N. Haala, F. Ackermann, GPS/INS in Photogrammetry. Tutorial Phowo '97. Stuttgart, Germany, 1997.
48 Dorota A., Grejner-Brzezinska. Direct Sensor Orientation in Airborne and Land-based Mapping Applications. The Ohio State University Report, June 2001, No. 461: pp. 25-30.
49 袁修孝.GPS辅助空中三角测量原理及应用.2001.8,第一版,北京:测绘出版社.
50 E.M. Mikhail, K. Weerawong. Exploitation of linear features in surveying and photogrammetry. Journal of Surveying Engineering, 1997, 123(1): pp. 32-47.
51 张祖勋,张剑清,胡翔云.基于物方空间几何约束最小二乘匹配的建筑物半自动提取方法.武汉大学学报(信息科学版),2001,Vol.26(4):290-295
52 胡翔云.航空遥感影像线状地物与房屋的自动提取.武汉大学博士学位论文,2001.
53 G. Vosselman, J. de Knecht. Road Tracing by Profile Matching and Kalman Filtering. In: Automatic Extraction of Man-Made objects from Aerial and Space Images, Basel, Switzerland, Birkhauser Verlag, 1995, pp. 265-274.
54 Grun A, Li H H. Semiautomatic linear feature extraction by dynamic programming and LSB-Snakes. Photogrammetric Engineering & Remote Sensing, 1997, 63(8): pp. 985-995.
55 Ruskone, R. Road Network Automatic Extraction by Local Context Interpretation: Application To the Production of Cartographic Data. Ph. D. Thesis. Marne-La-Vallee University, France, 1996.
56 Vosselman, G., Gunst, M.D. Updating Road Maps by Context Reasoning. In: Grun, A., Baltsavias, E.P., Henricsson, O. (Eds.), Automatic Extraction of Manmade Objects from Aerial and Space Images (Ⅱ), Birkhauser Verlag, Basel, 1997, pp. 267-276.
57 Bordes, G., Giraudon, G., Jamet, O. Road Modeling Based on a Cartographic Database for Aerial Image Interpretation. In: Forstner, W., Pluemer, L. (Eds.), Semantic Modelling for the Acquisition of Topographic Information from Images and Maps, Birkhauser Verlag, Basel, 1997, pp. 23-139.
58 Chunsun Zhang. Updating of Cartographic Road Databases by Image Analysis. PhD. Dissertation in ETH Swiztzerland, No. 14934, Zurich: ETH, 2003
59 Zuxun Zhang, Hongwei Zhang, Jianqing Zhang. Automatic road extraction based snake and line photogrammetry, roceedings of SPIE-The International Society for Optical Engineering, 2003,5286(2): pp. 605-610.
1 王之卓.摄影测量原理.1979年10月,北京:测绘出版社.
2 李德仁,郑肇葆.解析摄影测量学,1992,北京:测绘出版社:pp.6-38.
3 张剑清,潘励,王树根.数字摄影测量学.2002年12月,武汉:武汉大学出版社.
4 Ayman Habib, Andinet Asmamaw, Devin Kelley, Mania May. Linear Features in Fhotogrammetry. Report in Feodetic Science and Surveying, Department of Civil and Envirinmental Engineering and Geodetic Science, The Ohio State University, January 2000, No. 450.
5 ZHANG Jian Qing, ZHANG Zu Xun. Strict Geometric Model Based on Affine Transformation for Remote Sensing Image with High Resolution, Int. Archives of ISPRS, 2002, Vol. ⅩⅩⅩⅣ, Part 3B, Comm. Ⅲ.
6 陈希孺,王松桂.近代实用回归分析.1988,桂林:广西人民出版社.
7 钱增波,刘靖宇,肖国超.航天摄影测量.1992,北京:解放军出版社.
8 燕琴,张祖勋,张剑清.异轨遥感CCD影像外方位元素的解求.武汉大学学报·信息科学版 2001.6,26(3):pp270-273.
9 黄玉琪.基于岭估计的SPOT影像外方位元素的解算方法.解放军测绘学院学报,1998.3,15(1):pp25-27.
10 燕琴,张剑清.结合AI方法解求SPOT影像外方位元素.遥感信息,2000.4:pp42-43.
11 V. Kratky. Rigorous Photogrammetric Processing of SPOT Images at CCM Canada. ISPRS Journal of Photogrammetry and Remote Sensing, 1989, 44: pp. 53-71.
12 V. Kratky. On-Line Aspects of Stereophotogrammetric Processing of SPOT Images. PE&RS, March 1989,55(3): pp. 311-316.
13 孙家捅 主编.遥感原理与应用.2003.2,武汉:武汉大学出版社,pp130-132.
14 许素芹,王同合,徐青,孟微波.利用Landsat TM图像更新地形图.郑州:测绘学院学报,第18卷增刊:pp.23-25.
15 丁纯勤,王大可,杨武年,刘登忠等.卫星遥感TMl:5万正射影像地图研制.地矿测绘,1996,第三期:pp.20-24.
16 濮国梁.TM、SPOT图像及INSAR技术在正射遥感影像制图中的综合应用.成都理工学院硕士学位论文,2000.
1 Hu, X., Z. Zhang, J. Zhang. An approach of semiautomated road extraction from aerial image based on template matching and neural network. International Archives of Photogrammetry and Remote Sensing, 2000, XXXIII(B3/2): pp. 994-999.
2 胡翔云。航空遥感影像线状地物与房屋的自动提取。武汉大学博士学位论文,2001。
3 Ivan Laptev, Helmut Mayer, Tony Lindeberg, Wolfgang Eckstein etc. Automatic extraction of roads from aerial images based on scale-space and snakes. Technical report CVAP240, ISRN KTH/NA/P-00/06-SE, March 2000.
4 C. Heipke, H.Mayer, C. Wiedemann, O. Jamet. Evaluation of Automatic Road Extraction. Proceedings of International Archives of Photogrammetry and Remote sensing, 1997, X X XII: pp. 47-56.
5 M. -F. Auclair Fortier, D. Ziou, C.Armenakis and S. Wang. Survey of Work on Road Extraction in Aerial and Satellite Images. Technical Report N. 247 in DMI,Universite de Sherbrooke.
6 Trinder, J. and Y. Wang. Automatic road extraction from aerial images. Digital Signal Processing, 1998,8: pp. 215-224.
7 Katartzis, A., H. Sahli, V. Pizurica, J. Cornelis. A model-bas ed approach to the automatic extraction of linear features from airborne images. IEEE trans. on Geoscience and Remote Sensing, 2001,39(9): pp. 2073-2079.
8 Mayer, H., C. Steger. Scale-space events and their link to abstraction for road extraction, ISPRS Journal of Photogrammetry and Remote Sensing, 1998,53: pp. 62-75.
9 Doucette, P., P. Agouris, A. Stefanidis, M. Musavi. Self-organised clustering for road extraction in classified imagery, ISPRS Journal of Photogrammetry and Remote Sensing, 2001,55: pp. 347-358.
10 Gruen, A., H. H Li. Semi-automatic linear feature extraction by dynamic programming and LSBsnakes, Photogrammtric Engineering and Remote Sensing, 1997,63(8): pp. 985-995.
11 Vosselman, G., J. Knecht. Road tracing by profile matching and Kalman filtering. Automatic Extraction of Man-made Objects from Aerial and Space Images (A. Gruen, 0. Kuebler and P. Agouris, editors), Birkhauser, Basel, 1997: pp. 265-274.
12 Gruen, A., P. Agouris, H. H Li. Linear feature extraction with dynamic programming and globally enforced least squares matching. Automatic Extraction of Man-made Objects from Aerial and Space Images (A. Gruen, O. Kuebler and P. Agouris, editors), Birkhauser, Basel, 1995, pp. 83-94.
13 Bajcsy R, MTavakoli. Computer recognition of road from satellite pictures. IEEE Trans on systems, man and Cbybernetics, 1976, 6(9): pp. 623-637.
14 L Quam. Road tracking and anomaly detection in aerial imagery. Proceedings: DAPRA Image Understanding Workshop, 1978: pp. 51-55.
15 R Nevatia, K R Babu. Linear feature extraction and description. IEEE CGIP, 1980: pp. 257-269.
16 Fischler M A, et. al. Detection of Roads and linear structures in low-resolution aerial imagery using a multisource kmowledge integration technique. CGIP, 1981 (15): pp. 201-223.
17 Zhu M L, P S Yeh. Automatic road network extraction on aerial photographs. Computer Vision and Pattern Recognition. IEEE Computer Society Press, 1986: pp. 34-40.
18 Mckeown D, J Denlinger. Comparative methods for road tracking in aerial imagery. IEEE Proc. On CVPR,Michigan, 1988: pp. 662-672.
19 Lemmens M, et. al. Linear feature extraction and road recognition from large scale digital aerial images. In: IAPRS, 1988, Vol. 27, Part B8: pp.20-31.
20 M Barzohar, D B Cooper. Automatic finding of main road in aerial images by using geometric-stochastic models and estimation. IEEE CVPR, 1993, Vol 7
21 Heipke C, Steger C, Multhammer R. A gierarchical approach to automatic road extraction from aerial imagery. In: D M Mckeown Jr, I J Dowman(eds), Integrating Photogrammetric Techniques with Scene analysis and Machine Vision Ⅱ,Pro. SPIE 2486, 1995: pp. 222-231.
22 Sylvain A, et. al. From manual to automatic stereoplotting: evaluation of different road network capture processes. IAPRS, Viena, 1996, ⅩⅩⅪ Part B3: pp.14-17.
23 Renaud R, sylvain, et. al. Road network interpretation : a topological hypothsis driven system. ISPRS Comm. Ⅲ working Group 3,1996: pp.711-717.
24 J Trinder, Wang Y D. Knowledge based road interpretation in aerial images. In: IAPRS 32 PART 4,1998: pp. 635-640.
25 Tonics R, Growe S. Knowledge based road extraction from multisensor imagery. ISPRS Comm. Ⅲ working Group 4,1998.
26 H A Karimi, et. al. Techniques for automated extraction of roadway inventory features from high-resolution satellite imagery. Geocato International, 1999,14(2): pp.5-16.
27 Baumgartner A. Extraction of roads from aerial imagery based on grouping and local context. In International Archives of Photogrammetry and Remote Sensing, 1998, 32(3╱1), pp.196-201.
28 文贡坚,王润生.从航空遥感图像中自动提取主要道路.软件学报,2000,11(7):pp.957-964.
29 Grun A, Li H H. Semiautomatic linear feature extraction by dynamic programming and LSB-Snakes. Photogrammetric Engineering & Remote Sensing, 1997,63(8): pp. 985-995.
30 Trinder J, Li H H. Semiautomatic feature extraction by snake. In A. Gruen, O. Kubler, P. Agouris(ed), Automatic extraction of manmade objects from aerial and space images. Birkhauser verlag, 1995: pp.95-104.
31 林宗坚,刘少创.航空影像中道路提取的Snake方法.武汉测绘科技大学学报,1996(3).
32 Li H H. Semiautomatic road extract from satellite and aerial images. PhD. Dissertation in ETH Swiztzerland, No 12101, Zurich:ETH, 1997.
33 Heipke C, et. al. Semiautomatic extraction of roads from aerial images. In IAPRS Comm. Ⅲ workshop, 1994, Munich: pp. 353-359.
34 Chunsun Zhang. Updating of Cartographic Road Databases by Image Analysis.PhD. Dissertation in ETH Swiztzerland, No. 14934, Zurich: ETH, 2003
35 Kenneth.R.Castleman,(朱志刚,林学门言,石定机 译).数字图像处理.1998.9,北京:电子工业出版社,pp.60-300.
36 张力,张祖勋,张剑清.Wallis 滤波在影像匹配中的应用.武汉测绘科技大学学报,1999.3,24(1).
37 张祖勋,张剑清.数字摄影测量学.1996,武汉:武汉测绘科技大学出版社.
38 郑南宁.计算机视觉与模式识别.1998,北京:国防工业出版社.
39 Canny, J. A Computational Approach to Edge Detection. IEEE trans. on Pattern Analysis and Machine Intelligence, 1986.11, PAMI-8(6): pp. 679-698.
40 Ackermann F. High Precision Digital Image Correlation. Proceedings of the 39th Photogrammetric Week, University of Stuttgart, 1983.
41 Gruen A. Adaptive least square correlation: a powerful image matching technique. South African Journal of Photogrammetry and Remote Sensing, 1985,14(3): pp. 175-187.
42 Gruen A, D Stallmann. High accuracy dimensional measurement using non-target object features. IAPRS, 1992, ⅩⅩⅠⅩ Part BS, Washington: pp. 694-700.
43 张永军.基于序列图像的工业钣金件三维重建与视觉检测.武汉大学博士学位论文,No.10486,2002.
44 於宗俦,鲁林成.测量平差基础.1983,北京:测绘出版社.
45 李培华,张田文.主动轮廓线模型(蛇模型)综述.软件学报,2000,11(6):pp.751-757.
46 M. Kass, A. Witkin, D. Terzopoulos. Snakes: Active Contour Models. International Journal of Computer Vision, 1988,1(4): pp. 321-331.
47 冯炯,戚飞虎.Snake成长阶段的分析方法.上海交通大学学报,1999.9,33(9).
48 Amini A, Weymouth T, Jain R. Using dynamic programming for solving variational problems in vision. IEEE Trans. on PAMI. 1990,12(9): pp.855-867.
49 Geiger D, Gupta A, Costa L A, Vlontzos J. Dynamical Programming for Detecting, Tracking and Matching Deformable Contours. IEEE Trans. on PAMI. 1995, 17(3): pp.294-302.
50 Cohen L D, Cohen I. A finite element method applied to new active contour models and 3D reconstruction from cross sections. In: Jsuji S, Kak A, Eklundh I O eds. Proceedings of the 3rd International Conference on Computer Vision. Osaka, Japan: IEEE Computer Society Press, 1990: pp.587-591.
51 W. Neuenschwander, P. Fua, L. Iverson, G. Székely, O. Kubler, Ziplock Snakes. International Journal of Computer Vision, 1994.
52 陈洪.对snake模型的研究.上海:复旦大学硕士学位论文,2002:pp.5-8
1 Heikkinen, J. and Laiho, A. The use of linear features as reference datum in digital map revision. ISPRS, Washington D.C., U.S.A., 1992, Vol. XXIX, Part B4: pp. 500-506.
2 Aymsn Habib, Andinet Asmamaw, Devin Kelley, Mania May. Linear Features in Fhotogrammetry. Report in Feodetic Science and Surveying, Department of Civil and Envirinmental Engineering and Geodetic Science, The Ohio State University, No.450, January 2000.
3 F.A. van den Heuvel. A Line-photogra~metricmathematical model for the reconstructionof polyhedral objects, in Videometrics VI, Sabry F. El-Hakim (ed.), Proceedings of SPIE,1999, Vol. 3641, ISBN 0-8194-3112-5: pp. 60-71.
4 王之直摄影测量原理.1979.10,北京:测绘出版社.
5 李德仁,郑肇葆.解析摄影测量学.1992,北京:测绘出版社:pp.6-38.
6 张祖勋,张剑清.数字摄影测量学的发展和应用.测绘通报,1996(6):pp.12-17.
7 张祖勋,张剑清.数字摄影测量学.1996,武汉:武汉测绘科技大学出版社.
8 Heikkinen, J. and Laiho, Ao The use of linear features as reference datum in digitalmap revision. ISPRS, Washington D.C., U.S.A., 1992, Vol. XXIX, Part B4: pp. 500-506.
9 Kubik, K. Relative and AbsiluteOrientation Based on Linear Feature. ISPRS Journal ofPhotogrammetry and Remote Sensing, 1988, Vol. 46: pp. 199-20~
10 E.M.Mikhail,K.Weerawong.Exploitation of linear features in surveying andphotogrammetry. Journal of Surveying Engineering, 1997,123(1): pp. 32-47.
11 HsiangTseng Lin. Autonomous Recovery of Exterior Orientation of Imagery usingFree-FormLinear Feature. Ph.D Dissertation of Ohio State University, UMI Number:3049072,2002.
12 GUlch, E. Automatic Control Point Measurement. In: Photogrammetric Week '95, Fritsch,D., Hobble, D.(Eds.), Wichmann Verlag, Heidelberg, 1995: pp. 185-196.
13 Zuxun Zhang, Hongwei Zhang, Jianqing Zhang. Automatic road extraction based snake and line photogrammetry, proceedings of SPIE-The International Society for Optical Engineering, 2003,5286(2): pp. 605-610.
14 Schenk T. Towards automatic aerial triangulation. ISPRS Journal of Photogrammetry and Remote Sensing, 1997,52: pp. 110-121.
15 Mulawa D.C.,Mikhail E.D., Photogrammetric Treatment of Linear Features. International Archives of Photogrammetry and Remote Sensing, 1988,27(B10): pp. 282-393.
16 AckermannF. High Precision Digital Image Correlation. Proceedings of the 39th Photogrammetric Week, University of Stuttgart, 1983.
17 Gruen A Adaptive least square correlation: a powerful image matching technique. South African Journal of Photogrammetry and Remote Sensing, 1985,14(3): pp. 175-187.
18 Forsmer W, Gulch E, A Fast Operator for Detection and precise Location of Distinct Points, Comersand Centres of Circular Features. Intercommision Conference on Fast Processing of Photogrammetric Data, In-terlaken, Switzerland, 1987.
19 张祖勋,张剑清,吴晓良,跨接法概念之扩展及整体影像匹配,武汉测绘科技大学学报,1991,16(3).
20 Halla, N., Vosselman, G. Recognition of road and river patterns by relational matching. Ibid., 1992,29(B3): pp. 969-975.
21 Galch, E. Using Feature Extraction to Prepare the Automated Measurement of Control Points in Digital Aerial Triangulation. ISPRS Comm, Ⅲ Symposium, Munich, IAP, 1994, Vol. 30-3/1.
22 C. Drewniok, K. Rohr. Automatic Exterior Orientation of Aerial Images in Urban Environments. International Archives of Photogrammetry and Remote Sensing. 1996, Vol. ⅩⅩⅩⅠ part B3: pp. 146-152.
23 Habib, A. F., Kelley, D., Asmamaw, A. New approach to solving matching problems in photogrammetry. International Archives of Photogrammetry and Remote Sensing, Amsterdam, the Netherlands, 2000,33(B2): pp. 257-264.
24 Tommaselli A., Tozzi C. A recursive approach to space resection using straight lines. Photogrammetric Engineering and remote Sensing, 1996, 62(Ⅰ): pp. 57-66.
25 Tankovich J. Multiple photograph resection and intersection using linear features. M.S. Thesis. Department of Geodetic Science and Surveying, The Ohio State University, Columbus, Ohio, 1991.
26 Tommaselli. A., Lugnani. J. An Alternative Mathematical Model to the Collinearity Equation using Straight Features. International Archives of Photogrammetry and remote Sensing, 1988,27(B3): pp. 765-774.
27 Zuxun Zhang, Jianqing Zhaag. Generalized Point Photogrammetry and its Application. ⅩⅩth ISPRS Congress Commission 5, 12-23 July 2004, Istanbul, Turkey.
28 Paul E. Debevec, Camillo J. Taylor, Jitendra Malik. Modeling and Rendering Architecture from Photographs. In SIGGRAPH'96, August 1996.
29 於宗俦,鲁林成.测量平差基础.1983,北京:测绘出版社.
1 Mulawa D.C.,Mikhail E.D. Photogrammetric Treatment of Linear Features. International Archives of Photogrammetry and Remote Sensing, 1988,27(B10): pp.282-393.
2 HsiangTseng Lin. Autonomous Recovery of Exterior Orientation of Imagery using Free-Form Linear Feature. Ph.D Dissertation of Ohio State University, UMI Number:3049072, 2002.
3 Ayman Habib, Andinet Asmamaw, Devin Kelley, Manja May. Linear Features in Fhotogrammetry. Report in Feodetic Science and Surveying, Department of Civil and Envirinmental Engineering and Geodetic Science, The Ohio State University, No. 450, January 2000.
4 Roberts. K. A new representation for a line. Proceedings. International Conference. Computer Vision and Pattern Recognition, 1988: pp. 635-640.
5 Ayache. N., Faugeras. O. MAintaining representations of the environment of a mobile robot. IEEE transactions. Robotics Automation, 1989,5(6): pp. 809-819.
6 张继贤,张永红,林宗坚.SPOT影像像点位移的研究.测绘科学,2000,25(1):pp.19-22.
7 Young-ran Lee. Pose estimation of line cameras using linear features. Ph.D Dissertation of Ohio State University, UMI Number:3049066, 2002.
8 Garry H. Zalmanson. Hierarchical recovery of exterior orientation from parametric and natural 3-D curves. Ph. D Dissertation of Ohio State University, UMI Number:9962467, 2000.
9 王之卓,摄影测量原理.1979.10,北京:测绘出版社.
10 於宗俦,鲁林成.测量平差基础.1083,北京:测绘出版社.
11 胡翔云.航空遥感影像线状地物与房屋的自动提取.武汉大学博士学位论文,2001.
12 李德仁,袁修孝.误差处理与可靠性理论.2002.7,第一版,武汉:武汉大学出版社.
13 陶本藻,刘宗泉.总述粗差估计与检验.四川测绘,1999,22(2):pp.56-59.
14 崔希璋,於宗俦,陶本藻等.广义测量平差(新版).2001.2,第一版,武汉:武汉测绘科技大学出版社.
15 李德仁,郑肇葆.解析摄影测量学.1992,北京:测绘出版社:pp.159-165.
16 张祖勋,张剑清.数字摄影测量学.1996,武汉:武汉测绘科技大学出版社.
2 李德仁,郑肇葆.解析摄影测量学.1992,北京:测绘出版社,pp.4-5.
3 张祖勋,张剑清.数字摄影测量学的发展和应用.测绘通报,1996(6):pp.12-17
4 李德仁.摄影测量与遥感的现状及发展趋势.武汉测绘科技大学学报,2000,25(1):pp.1-5
5 张祖勋,张剑清,张力.数字摄影测量学发展的机遇与挑战.武汉测绘科技大学学报,2000,25(1):pp.7-11.
6 李德仁等.摄影测量与遥感概论.2001,北京:测绘出版社.
7 Peter P. Product survey on digital photogrammetry workstation. GIM international, 2001(4): pp. 69-73.
8 Konecny G. Future prospects of mapping from space. Proceeding of SIST' 98. Wuhan: WTUSM, 1998: PP. 143-159.
9 李德仁,周月琴.空间测图——现状与未来.测绘通报,2000(1):pp.3-7.
10 粱家琳.地物要素变化探测与地图更新自动化方法.测绘科技通讯,1997(4):pp.15-17
11 蒋捷,陈军.基础地理信息数据库更新的若干思考.测绘通报,2000(5).
12 I. J. DOWAN. Automating image registration and absolute orientation: solutions and problems. Photogrammetric Record, 16(91)(April 1998): pp. 5-18.
13 Lisa Gottesfeld Brown. A Survey of Image Registration Technology. Report of Department of Computer Science Columbia University New York, January 12, 1992.
14 Hui Li, B.s. Manjunath, Sanjit K. Mitra. A Contour-Based Approach to Multisensor Image Registration. IEEE Transactions On Image Process, March 1995, 4(3): pp320-334.
15 Xiaolong Dai, Siamak Khorram. A Feature-Based Image Registration Algorithm Using Improved Chain-Code Representation Combined with Invariant Moments. IEEE Transactions On Geoscience and Remote Sensing, September 1999,37(5),pp. 2351-2362.
16 C. Drewniok, K. Rohr. Automatic Exterior Orientation of Aerial Images in Urban Environments. International Archives of Photogrammetry and Remote Sensing, 1996, Vol. ⅩⅩⅩⅠ part B3 pp. 146-152.
17 Stefan Growe, Ralf Tonjes. A Knowledge Based Approach to Automatic Image Registraction. International Conference on Image Processing(ICIP'97),scheduled for October 26-29,1997 in Santa Barbara, CA, USA, IEEE Published
18 JUrgen BUckner. Model Based Road Extraction For The Registration And Interpretation Of Remote Sensing Data. ISPRS Commission IV Symposium on' GIS-Between Visions and Applications, Stuttgart, Germany, 7.9.-10.9.98.
19 F. A. van den Heuvel. Exterior Orientation using Coplanar Parallel Lines. Proceedings of the 10th Scandinavian Conference on Image Analysis, Lappeenranta, ISBN 951-764-145-1, 1997: pp. 71-78.
20 F.A. van den Heuvel. ALine-photogrammetric mathematical model for the reconstruction of polyhedral objects, in Videometrics VI, Sabry F. EI-Hakim (ed.), Proceedings of SPIE Vol. 3611, ISBN 0-8194-3112-5,1999: pp. 60-71.
21 Ian Dowman. Automated Procedures For Integration Of Satellite Images And Map Data For Change Detection: The Archangel Project IAPRS. Vol. 32,Part 4"GIS-Between Visions and Applications', Stuttgart, 1998: pp. 162-169.
22 M.J. SMITH, D.W.G. PARK. Towards A New Approach.For Absolute And Exterior Orientation. Photogrammetric Record, 16(94) (October 1999): pp. 617-623
23 Qiang Ji. A robust linear least-squares estimation of camera exterior orientation using multiple geometric features. ISPRS Journal of Photogrammetry & Remote Sensing, 2000(55) : pp. 75-93.
24 Heiner HILD, Norbert HAALA, Dieter FRITSCH. A Strategy For Automatic Image To Map Registration. IAPRS, Vol. XXXIII, Amsterdam, 2000 (Institute for Photogrammetry (ifp), Stuttgart University, Germany
25 Elli Petsa, George E. Karras. Constrained Line-Photogrammetric 3d Reconstruction From Stereopairs. IAPRS, Vol.XXXIII, Amsterdam, 2000 (Institute for Photogrammetry (ifp), Stuttgart University, Germany
26 Taravudh Tipdecho. Automatic Image Registration between Image and Object Spaces. Proceedings of the Open source GIS-GRASS users conference 2002, Trento, Italy, September 2002: pp. 11-13.
27 Ayman Habib, Michel Morgan, Young-Ran Lee. Bundle Adjustment With Selfcalibration Using Straight Lines. Photogrammetric Record, October, 2002.
28 Joachim Hohle. Automated Orientation of Aerial Images. I: Bildteknik, Image Science, 2002, Nr. 1. s. pp. 91-101.
29 Habib, A. F., Kelley, D., Asmamaw, A., New approach to solving matching problems in photogrammetry. International Archives of Photogrammetry and Remote Sensing, Amsterdam, the Netherlands, 2000, 33(B2): pp. 257-264.
30 Habib, A. F., Kelley D., Single photo resection using the modified Hough transform. Journal of Photogrammetric Engineering & Remote Sensing, 2001, 67(8): pp909-914.
31 Habib, A. F. and Kelley, D., Automatic relative orientation of large scale imagery over urban areas using modified iterated Hough transform. International Journal of Photogrammetry & Remote Sensing, 2001,56(2001): pp.29-41.
32 HsiangTseng Lin. Autonomous Recovery of Exterior Orientation of Imagery using Free-Form Linear Feature. Ph. D Dissertation of Ohio State University, UMI Number:3049072, 2002.
33 Garry H. Zalmanson. Hierarchical recovery of exterior orientation from parametric and natural 3-D curves. Ph. D Dissertation of Ohio State University, UMI Number:9962467, 2000.
34 Young-ran Lee. Pose estimation of line cameras using linear features. Ph. D Dissertation of Ohio State University, UMI Number:3049066, 2002.
35 Gulch, E. Using Feature Extraction to Prepare the Automated Measurement of Control Points in Digital Aerial Triangulation. ISPRS Comm. III Symposium, Munich, IAP 1994, Vol. 30-3/1.
36 Gulch, E. Automatic Control Point Measurement. In: Photogrammetric Week ' 95, Fritsch, D., Hobbie, D. (Eds.),Wichmann Verlag, Heidelberg, 1995: pp. 185-196.
37 Drewniok, C., Rohr, K., Automatic Exterior Orientation of Aerial Images in Urban Environments. In: International Archives of Photogrammetry and Remote Sensing, 1992, vol. 31,B3,pp. 146-152.
38 Hahn, M., Kiefner, M., Quednau, A., Hinz, E., Semi-Automatic Measurement of Signalized Ground Control Points at Digital Photogrammetric Workstations. In: International Archives of Photogrammetry and Remote Sensing, 1996, vol. 31, 83, pp. 291-296.
39 Schickler W., Feature Matching for Outer Orientation of Single Images Using 3-D Wireframe Control Points. In: International Archives of Photogrammetry and Remote Sensing, 1992, vol. 29,83.
40 Vosselman, G. and Haala, N., Erkennung topographischer Pabpunkte durch relationale Zuordnung. ZPF 6/92,1992.
41 Halla, N., Vosselman, G., Recognition of road and river patterns by relational matching. Ibid., 1992,29(83): pp. 969-975.
42 Orgado, A., Do,an, I., A procedure for automatic absolute orientation using aerial photographs and a map. ISPRS Journal of Photogrammetry & Remote Sensing, 1997, 52(4): pp. 169-182.
43 Ayman Habib, Andinet Asmamaw, Devin Kelley, Mania May. Linear Features in Fhotogrammetry. Report in Feodetic Science and Surveying, Department of Civil and Enviriamental Engineering and Geodetic Science, The Ohio State University, January 2000, No. 450.
44 Heipke, C., Automation of interior, relative, and absolute orientation. ISPRS Journal of Photogr~metry & Remote Sensing, 1997, 52(1): pp. 1-19.
45 Heikkinen, J., Laiho, A. The use of linear features as reference datum in digital map revision. ISPRS, Washington D.C., U.S.A., 1992, Vol. ⅩⅩⅠⅩ, Part 84, pp. 500-506.
46 Ackermann, F. Geo-Kodierung ohne PaBpunkte. In: Geo-Informations-Systeme, 1997, 10(2): pp. 28-32.
47 Fritsch, D., M. Cramer, M. Englich, N. Haala, F. Ackermann, GPS/INS in Photogrammetry. Tutorial Phowo '97. Stuttgart, Germany, 1997.
48 Dorota A., Grejner-Brzezinska. Direct Sensor Orientation in Airborne and Land-based Mapping Applications. The Ohio State University Report, June 2001, No. 461: pp. 25-30.
49 袁修孝.GPS辅助空中三角测量原理及应用.2001.8,第一版,北京:测绘出版社.
50 E.M. Mikhail, K. Weerawong. Exploitation of linear features in surveying and photogrammetry. Journal of Surveying Engineering, 1997, 123(1): pp. 32-47.
51 张祖勋,张剑清,胡翔云.基于物方空间几何约束最小二乘匹配的建筑物半自动提取方法.武汉大学学报(信息科学版),2001,Vol.26(4):290-295
52 胡翔云.航空遥感影像线状地物与房屋的自动提取.武汉大学博士学位论文,2001.
53 G. Vosselman, J. de Knecht. Road Tracing by Profile Matching and Kalman Filtering. In: Automatic Extraction of Man-Made objects from Aerial and Space Images, Basel, Switzerland, Birkhauser Verlag, 1995, pp. 265-274.
54 Grun A, Li H H. Semiautomatic linear feature extraction by dynamic programming and LSB-Snakes. Photogrammetric Engineering & Remote Sensing, 1997, 63(8): pp. 985-995.
55 Ruskone, R. Road Network Automatic Extraction by Local Context Interpretation: Application To the Production of Cartographic Data. Ph. D. Thesis. Marne-La-Vallee University, France, 1996.
56 Vosselman, G., Gunst, M.D. Updating Road Maps by Context Reasoning. In: Grun, A., Baltsavias, E.P., Henricsson, O. (Eds.), Automatic Extraction of Manmade Objects from Aerial and Space Images (Ⅱ), Birkhauser Verlag, Basel, 1997, pp. 267-276.
57 Bordes, G., Giraudon, G., Jamet, O. Road Modeling Based on a Cartographic Database for Aerial Image Interpretation. In: Forstner, W., Pluemer, L. (Eds.), Semantic Modelling for the Acquisition of Topographic Information from Images and Maps, Birkhauser Verlag, Basel, 1997, pp. 23-139.
58 Chunsun Zhang. Updating of Cartographic Road Databases by Image Analysis. PhD. Dissertation in ETH Swiztzerland, No. 14934, Zurich: ETH, 2003
59 Zuxun Zhang, Hongwei Zhang, Jianqing Zhang. Automatic road extraction based snake and line photogrammetry, roceedings of SPIE-The International Society for Optical Engineering, 2003,5286(2): pp. 605-610.
1 王之卓.摄影测量原理.1979年10月,北京:测绘出版社.
2 李德仁,郑肇葆.解析摄影测量学,1992,北京:测绘出版社:pp.6-38.
3 张剑清,潘励,王树根.数字摄影测量学.2002年12月,武汉:武汉大学出版社.
4 Ayman Habib, Andinet Asmamaw, Devin Kelley, Mania May. Linear Features in Fhotogrammetry. Report in Feodetic Science and Surveying, Department of Civil and Envirinmental Engineering and Geodetic Science, The Ohio State University, January 2000, No. 450.
5 ZHANG Jian Qing, ZHANG Zu Xun. Strict Geometric Model Based on Affine Transformation for Remote Sensing Image with High Resolution, Int. Archives of ISPRS, 2002, Vol. ⅩⅩⅩⅣ, Part 3B, Comm. Ⅲ.
6 陈希孺,王松桂.近代实用回归分析.1988,桂林:广西人民出版社.
7 钱增波,刘靖宇,肖国超.航天摄影测量.1992,北京:解放军出版社.
8 燕琴,张祖勋,张剑清.异轨遥感CCD影像外方位元素的解求.武汉大学学报·信息科学版 2001.6,26(3):pp270-273.
9 黄玉琪.基于岭估计的SPOT影像外方位元素的解算方法.解放军测绘学院学报,1998.3,15(1):pp25-27.
10 燕琴,张剑清.结合AI方法解求SPOT影像外方位元素.遥感信息,2000.4:pp42-43.
11 V. Kratky. Rigorous Photogrammetric Processing of SPOT Images at CCM Canada. ISPRS Journal of Photogrammetry and Remote Sensing, 1989, 44: pp. 53-71.
12 V. Kratky. On-Line Aspects of Stereophotogrammetric Processing of SPOT Images. PE&RS, March 1989,55(3): pp. 311-316.
13 孙家捅 主编.遥感原理与应用.2003.2,武汉:武汉大学出版社,pp130-132.
14 许素芹,王同合,徐青,孟微波.利用Landsat TM图像更新地形图.郑州:测绘学院学报,第18卷增刊:pp.23-25.
15 丁纯勤,王大可,杨武年,刘登忠等.卫星遥感TMl:5万正射影像地图研制.地矿测绘,1996,第三期:pp.20-24.
16 濮国梁.TM、SPOT图像及INSAR技术在正射遥感影像制图中的综合应用.成都理工学院硕士学位论文,2000.
1 Hu, X., Z. Zhang, J. Zhang. An approach of semiautomated road extraction from aerial image based on template matching and neural network. International Archives of Photogrammetry and Remote Sensing, 2000, XXXIII(B3/2): pp. 994-999.
2 胡翔云。航空遥感影像线状地物与房屋的自动提取。武汉大学博士学位论文,2001。
3 Ivan Laptev, Helmut Mayer, Tony Lindeberg, Wolfgang Eckstein etc. Automatic extraction of roads from aerial images based on scale-space and snakes. Technical report CVAP240, ISRN KTH/NA/P-00/06-SE, March 2000.
4 C. Heipke, H.Mayer, C. Wiedemann, O. Jamet. Evaluation of Automatic Road Extraction. Proceedings of International Archives of Photogrammetry and Remote sensing, 1997, X X XII: pp. 47-56.
5 M. -F. Auclair Fortier, D. Ziou, C.Armenakis and S. Wang. Survey of Work on Road Extraction in Aerial and Satellite Images. Technical Report N. 247 in DMI,Universite de Sherbrooke.
6 Trinder, J. and Y. Wang. Automatic road extraction from aerial images. Digital Signal Processing, 1998,8: pp. 215-224.
7 Katartzis, A., H. Sahli, V. Pizurica, J. Cornelis. A model-bas ed approach to the automatic extraction of linear features from airborne images. IEEE trans. on Geoscience and Remote Sensing, 2001,39(9): pp. 2073-2079.
8 Mayer, H., C. Steger. Scale-space events and their link to abstraction for road extraction, ISPRS Journal of Photogrammetry and Remote Sensing, 1998,53: pp. 62-75.
9 Doucette, P., P. Agouris, A. Stefanidis, M. Musavi. Self-organised clustering for road extraction in classified imagery, ISPRS Journal of Photogrammetry and Remote Sensing, 2001,55: pp. 347-358.
10 Gruen, A., H. H Li. Semi-automatic linear feature extraction by dynamic programming and LSBsnakes, Photogrammtric Engineering and Remote Sensing, 1997,63(8): pp. 985-995.
11 Vosselman, G., J. Knecht. Road tracing by profile matching and Kalman filtering. Automatic Extraction of Man-made Objects from Aerial and Space Images (A. Gruen, 0. Kuebler and P. Agouris, editors), Birkhauser, Basel, 1997: pp. 265-274.
12 Gruen, A., P. Agouris, H. H Li. Linear feature extraction with dynamic programming and globally enforced least squares matching. Automatic Extraction of Man-made Objects from Aerial and Space Images (A. Gruen, O. Kuebler and P. Agouris, editors), Birkhauser, Basel, 1995, pp. 83-94.
13 Bajcsy R, MTavakoli. Computer recognition of road from satellite pictures. IEEE Trans on systems, man and Cbybernetics, 1976, 6(9): pp. 623-637.
14 L Quam. Road tracking and anomaly detection in aerial imagery. Proceedings: DAPRA Image Understanding Workshop, 1978: pp. 51-55.
15 R Nevatia, K R Babu. Linear feature extraction and description. IEEE CGIP, 1980: pp. 257-269.
16 Fischler M A, et. al. Detection of Roads and linear structures in low-resolution aerial imagery using a multisource kmowledge integration technique. CGIP, 1981 (15): pp. 201-223.
17 Zhu M L, P S Yeh. Automatic road network extraction on aerial photographs. Computer Vision and Pattern Recognition. IEEE Computer Society Press, 1986: pp. 34-40.
18 Mckeown D, J Denlinger. Comparative methods for road tracking in aerial imagery. IEEE Proc. On CVPR,Michigan, 1988: pp. 662-672.
19 Lemmens M, et. al. Linear feature extraction and road recognition from large scale digital aerial images. In: IAPRS, 1988, Vol. 27, Part B8: pp.20-31.
20 M Barzohar, D B Cooper. Automatic finding of main road in aerial images by using geometric-stochastic models and estimation. IEEE CVPR, 1993, Vol 7
21 Heipke C, Steger C, Multhammer R. A gierarchical approach to automatic road extraction from aerial imagery. In: D M Mckeown Jr, I J Dowman(eds), Integrating Photogrammetric Techniques with Scene analysis and Machine Vision Ⅱ,Pro. SPIE 2486, 1995: pp. 222-231.
22 Sylvain A, et. al. From manual to automatic stereoplotting: evaluation of different road network capture processes. IAPRS, Viena, 1996, ⅩⅩⅪ Part B3: pp.14-17.
23 Renaud R, sylvain, et. al. Road network interpretation : a topological hypothsis driven system. ISPRS Comm. Ⅲ working Group 3,1996: pp.711-717.
24 J Trinder, Wang Y D. Knowledge based road interpretation in aerial images. In: IAPRS 32 PART 4,1998: pp. 635-640.
25 Tonics R, Growe S. Knowledge based road extraction from multisensor imagery. ISPRS Comm. Ⅲ working Group 4,1998.
26 H A Karimi, et. al. Techniques for automated extraction of roadway inventory features from high-resolution satellite imagery. Geocato International, 1999,14(2): pp.5-16.
27 Baumgartner A. Extraction of roads from aerial imagery based on grouping and local context. In International Archives of Photogrammetry and Remote Sensing, 1998, 32(3╱1), pp.196-201.
28 文贡坚,王润生.从航空遥感图像中自动提取主要道路.软件学报,2000,11(7):pp.957-964.
29 Grun A, Li H H. Semiautomatic linear feature extraction by dynamic programming and LSB-Snakes. Photogrammetric Engineering & Remote Sensing, 1997,63(8): pp. 985-995.
30 Trinder J, Li H H. Semiautomatic feature extraction by snake. In A. Gruen, O. Kubler, P. Agouris(ed), Automatic extraction of manmade objects from aerial and space images. Birkhauser verlag, 1995: pp.95-104.
31 林宗坚,刘少创.航空影像中道路提取的Snake方法.武汉测绘科技大学学报,1996(3).
32 Li H H. Semiautomatic road extract from satellite and aerial images. PhD. Dissertation in ETH Swiztzerland, No 12101, Zurich:ETH, 1997.
33 Heipke C, et. al. Semiautomatic extraction of roads from aerial images. In IAPRS Comm. Ⅲ workshop, 1994, Munich: pp. 353-359.
34 Chunsun Zhang. Updating of Cartographic Road Databases by Image Analysis.PhD. Dissertation in ETH Swiztzerland, No. 14934, Zurich: ETH, 2003
35 Kenneth.R.Castleman,(朱志刚,林学门言,石定机 译).数字图像处理.1998.9,北京:电子工业出版社,pp.60-300.
36 张力,张祖勋,张剑清.Wallis 滤波在影像匹配中的应用.武汉测绘科技大学学报,1999.3,24(1).
37 张祖勋,张剑清.数字摄影测量学.1996,武汉:武汉测绘科技大学出版社.
38 郑南宁.计算机视觉与模式识别.1998,北京:国防工业出版社.
39 Canny, J. A Computational Approach to Edge Detection. IEEE trans. on Pattern Analysis and Machine Intelligence, 1986.11, PAMI-8(6): pp. 679-698.
40 Ackermann F. High Precision Digital Image Correlation. Proceedings of the 39th Photogrammetric Week, University of Stuttgart, 1983.
41 Gruen A. Adaptive least square correlation: a powerful image matching technique. South African Journal of Photogrammetry and Remote Sensing, 1985,14(3): pp. 175-187.
42 Gruen A, D Stallmann. High accuracy dimensional measurement using non-target object features. IAPRS, 1992, ⅩⅩⅠⅩ Part BS, Washington: pp. 694-700.
43 张永军.基于序列图像的工业钣金件三维重建与视觉检测.武汉大学博士学位论文,No.10486,2002.
44 於宗俦,鲁林成.测量平差基础.1983,北京:测绘出版社.
45 李培华,张田文.主动轮廓线模型(蛇模型)综述.软件学报,2000,11(6):pp.751-757.
46 M. Kass, A. Witkin, D. Terzopoulos. Snakes: Active Contour Models. International Journal of Computer Vision, 1988,1(4): pp. 321-331.
47 冯炯,戚飞虎.Snake成长阶段的分析方法.上海交通大学学报,1999.9,33(9).
48 Amini A, Weymouth T, Jain R. Using dynamic programming for solving variational problems in vision. IEEE Trans. on PAMI. 1990,12(9): pp.855-867.
49 Geiger D, Gupta A, Costa L A, Vlontzos J. Dynamical Programming for Detecting, Tracking and Matching Deformable Contours. IEEE Trans. on PAMI. 1995, 17(3): pp.294-302.
50 Cohen L D, Cohen I. A finite element method applied to new active contour models and 3D reconstruction from cross sections. In: Jsuji S, Kak A, Eklundh I O eds. Proceedings of the 3rd International Conference on Computer Vision. Osaka, Japan: IEEE Computer Society Press, 1990: pp.587-591.
51 W. Neuenschwander, P. Fua, L. Iverson, G. Székely, O. Kubler, Ziplock Snakes. International Journal of Computer Vision, 1994.
52 陈洪.对snake模型的研究.上海:复旦大学硕士学位论文,2002:pp.5-8
1 Heikkinen, J. and Laiho, A. The use of linear features as reference datum in digital map revision. ISPRS, Washington D.C., U.S.A., 1992, Vol. XXIX, Part B4: pp. 500-506.
2 Aymsn Habib, Andinet Asmamaw, Devin Kelley, Mania May. Linear Features in Fhotogrammetry. Report in Feodetic Science and Surveying, Department of Civil and Envirinmental Engineering and Geodetic Science, The Ohio State University, No.450, January 2000.
3 F.A. van den Heuvel. A Line-photogra~metricmathematical model for the reconstructionof polyhedral objects, in Videometrics VI, Sabry F. El-Hakim (ed.), Proceedings of SPIE,1999, Vol. 3641, ISBN 0-8194-3112-5: pp. 60-71.
4 王之直摄影测量原理.1979.10,北京:测绘出版社.
5 李德仁,郑肇葆.解析摄影测量学.1992,北京:测绘出版社:pp.6-38.
6 张祖勋,张剑清.数字摄影测量学的发展和应用.测绘通报,1996(6):pp.12-17.
7 张祖勋,张剑清.数字摄影测量学.1996,武汉:武汉测绘科技大学出版社.
8 Heikkinen, J. and Laiho, Ao The use of linear features as reference datum in digitalmap revision. ISPRS, Washington D.C., U.S.A., 1992, Vol. XXIX, Part B4: pp. 500-506.
9 Kubik, K. Relative and AbsiluteOrientation Based on Linear Feature. ISPRS Journal ofPhotogrammetry and Remote Sensing, 1988, Vol. 46: pp. 199-20~
10 E.M.Mikhail,K.Weerawong.Exploitation of linear features in surveying andphotogrammetry. Journal of Surveying Engineering, 1997,123(1): pp. 32-47.
11 HsiangTseng Lin. Autonomous Recovery of Exterior Orientation of Imagery usingFree-FormLinear Feature. Ph.D Dissertation of Ohio State University, UMI Number:3049072,2002.
12 GUlch, E. Automatic Control Point Measurement. In: Photogrammetric Week '95, Fritsch,D., Hobble, D.(Eds.), Wichmann Verlag, Heidelberg, 1995: pp. 185-196.
13 Zuxun Zhang, Hongwei Zhang, Jianqing Zhang. Automatic road extraction based snake and line photogrammetry, proceedings of SPIE-The International Society for Optical Engineering, 2003,5286(2): pp. 605-610.
14 Schenk T. Towards automatic aerial triangulation. ISPRS Journal of Photogrammetry and Remote Sensing, 1997,52: pp. 110-121.
15 Mulawa D.C.,Mikhail E.D., Photogrammetric Treatment of Linear Features. International Archives of Photogrammetry and Remote Sensing, 1988,27(B10): pp. 282-393.
16 AckermannF. High Precision Digital Image Correlation. Proceedings of the 39th Photogrammetric Week, University of Stuttgart, 1983.
17 Gruen A Adaptive least square correlation: a powerful image matching technique. South African Journal of Photogrammetry and Remote Sensing, 1985,14(3): pp. 175-187.
18 Forsmer W, Gulch E, A Fast Operator for Detection and precise Location of Distinct Points, Comersand Centres of Circular Features. Intercommision Conference on Fast Processing of Photogrammetric Data, In-terlaken, Switzerland, 1987.
19 张祖勋,张剑清,吴晓良,跨接法概念之扩展及整体影像匹配,武汉测绘科技大学学报,1991,16(3).
20 Halla, N., Vosselman, G. Recognition of road and river patterns by relational matching. Ibid., 1992,29(B3): pp. 969-975.
21 Galch, E. Using Feature Extraction to Prepare the Automated Measurement of Control Points in Digital Aerial Triangulation. ISPRS Comm, Ⅲ Symposium, Munich, IAP, 1994, Vol. 30-3/1.
22 C. Drewniok, K. Rohr. Automatic Exterior Orientation of Aerial Images in Urban Environments. International Archives of Photogrammetry and Remote Sensing. 1996, Vol. ⅩⅩⅩⅠ part B3: pp. 146-152.
23 Habib, A. F., Kelley, D., Asmamaw, A. New approach to solving matching problems in photogrammetry. International Archives of Photogrammetry and Remote Sensing, Amsterdam, the Netherlands, 2000,33(B2): pp. 257-264.
24 Tommaselli A., Tozzi C. A recursive approach to space resection using straight lines. Photogrammetric Engineering and remote Sensing, 1996, 62(Ⅰ): pp. 57-66.
25 Tankovich J. Multiple photograph resection and intersection using linear features. M.S. Thesis. Department of Geodetic Science and Surveying, The Ohio State University, Columbus, Ohio, 1991.
26 Tommaselli. A., Lugnani. J. An Alternative Mathematical Model to the Collinearity Equation using Straight Features. International Archives of Photogrammetry and remote Sensing, 1988,27(B3): pp. 765-774.
27 Zuxun Zhang, Jianqing Zhaag. Generalized Point Photogrammetry and its Application. ⅩⅩth ISPRS Congress Commission 5, 12-23 July 2004, Istanbul, Turkey.
28 Paul E. Debevec, Camillo J. Taylor, Jitendra Malik. Modeling and Rendering Architecture from Photographs. In SIGGRAPH'96, August 1996.
29 於宗俦,鲁林成.测量平差基础.1983,北京:测绘出版社.
1 Mulawa D.C.,Mikhail E.D. Photogrammetric Treatment of Linear Features. International Archives of Photogrammetry and Remote Sensing, 1988,27(B10): pp.282-393.
2 HsiangTseng Lin. Autonomous Recovery of Exterior Orientation of Imagery using Free-Form Linear Feature. Ph.D Dissertation of Ohio State University, UMI Number:3049072, 2002.
3 Ayman Habib, Andinet Asmamaw, Devin Kelley, Manja May. Linear Features in Fhotogrammetry. Report in Feodetic Science and Surveying, Department of Civil and Envirinmental Engineering and Geodetic Science, The Ohio State University, No. 450, January 2000.
4 Roberts. K. A new representation for a line. Proceedings. International Conference. Computer Vision and Pattern Recognition, 1988: pp. 635-640.
5 Ayache. N., Faugeras. O. MAintaining representations of the environment of a mobile robot. IEEE transactions. Robotics Automation, 1989,5(6): pp. 809-819.
6 张继贤,张永红,林宗坚.SPOT影像像点位移的研究.测绘科学,2000,25(1):pp.19-22.
7 Young-ran Lee. Pose estimation of line cameras using linear features. Ph.D Dissertation of Ohio State University, UMI Number:3049066, 2002.
8 Garry H. Zalmanson. Hierarchical recovery of exterior orientation from parametric and natural 3-D curves. Ph. D Dissertation of Ohio State University, UMI Number:9962467, 2000.
9 王之卓,摄影测量原理.1979.10,北京:测绘出版社.
10 於宗俦,鲁林成.测量平差基础.1083,北京:测绘出版社.
11 胡翔云.航空遥感影像线状地物与房屋的自动提取.武汉大学博士学位论文,2001.
12 李德仁,袁修孝.误差处理与可靠性理论.2002.7,第一版,武汉:武汉大学出版社.
13 陶本藻,刘宗泉.总述粗差估计与检验.四川测绘,1999,22(2):pp.56-59.
14 崔希璋,於宗俦,陶本藻等.广义测量平差(新版).2001.2,第一版,武汉:武汉测绘科技大学出版社.
15 李德仁,郑肇葆.解析摄影测量学.1992,北京:测绘出版社:pp.159-165.
16 张祖勋,张剑清.数字摄影测量学.1996,武汉:武汉测绘科技大学出版社.