直线特征约束的资源3号卫星影像自检校平差

针对控制点获取较困难地区卫星影像定位精度不高的情况,对直线特征作为控制信息提升卫星影像定位精度进行了研究。以"像方直线上任意一点必然位于物方直线和投影中心所构成的平面"作为几何约束条件,通过对直线的参数化表示,建立了基于直线特征的共面模型;在该模型基础上,针对航天传感器的成像特点,分析建立了8标定参数的内方位元素模型和简化的外方位元素模型,最终构建了直线特征约束的卫星影像自检校平差模型。利用资源3号(ZY-3)卫星获取的华盛顿地区数据对构建的平差模型进行实验验证。结果表明,该模型能够解决缺乏地面控制点地区影像定位精度差的问题,可达到与常规自检校平差相同量级的精度。     

卫星遥感影像的区域网平差成图精度

从卫星遥感影像区域网平差模型出发,利用卫星影像附带的RPC模型以及像面的3种变换模型建立了卫星遥感影像区域网平差的数学模型.按照所构建的数学模型,对某地区4景IKONOS影像进行直接空间前方交会处理,获得满足1:10万成图精度要求的加密点;利用该4景影像进行无地面控制点的区域网平差处理,获得满足1:2.5万成图精度要求的加密点;利用4角点位置的控制点进行区域网平差,获得满足1:1万的成图精度要求的加密点.试验证实,卫星影像的区域网平差技术在卫星遥感对地目标定位中有较好的应用前景.     

卫星遥感影像的区域网平差成图精度

从卫星遥感影像区域网平差模型出发,利用卫星影像附带的RPC模型以及像面的3种变换模型建立了卫星遥感影像区域网平差的数学模型。按照所构建的数学模型,对某地区4景IKONOS影像进行直接空间前方交会处理,获得满足1∶10万成图精度要求的加密点;利用该4景影像进行无地面控制点的区域网平差处理,获得满足1∶2.5万成图精度要求的加密点;利用4角点位置的控制点进行区域网平差,获得满足1∶1万的成图精度要求的加密点。试验证实,卫星影像的区域网平差技术在卫星遥感对地目标定位中有较好的应用前景。     

基于RPC模型的高分辨率卫星影像精确定位

介绍高分辨率卫星影像RPC模型的定义及其解算方法,推导RPC模型立体定位的基本方程,在此基础上对RPC模型的区域网平差进行深入研究。IKONOS卫星数据的实验结果表明,RPC模型误差呈现较强的系统性,但通过物方或像方的补偿立体定位可达到优于1.3 M的定位精度,区域网平差是最优的定位方法,精度可达1.1 M。     

本期导读

缺少控制点的SPOT-5 HRS影像RPC模型区域网平差(李德仁，等)从卫星遥感影像区域网平差的模型出发，利用SPOT-5影像附带的参数拟合RPC模型参数，根据RPC模型和像面的仿射变换模型建立了卫星遥感影像区域网平差的数学模型。按照所构建的数学模型，对两个地区的SPOT-5 HRS影像进行     

基于同轨约束RFM的高分卫星影像区域网平差

高分辨率光学(简称"高分")卫星影像普遍以标准景的形式提供给用户,并附带有理多项式模型(rational function model,RFM)。尽管同一轨道高分影像的姿态和轨道误差较为稳定,然而由于RFM的参数没有清晰的物理意义,因此难以建立同一轨道影像间的几何约束关系。从条带影像与标准景影像的差异出发,考虑标准景影像的分景效应以及积分时间差异的影响,提出了基于像方多项式模型的同轨约束方法,可对同轨道、不连续的标准景影像进行约束,实现基于同轨约束的高分卫星影像区域网平差。通过用我国资源三号(ZY-3)测绘卫星同轨7景三线阵立体影像和印度IRS-P5卫星两轨4景两线阵立体影像进行实验,证明所提出的同轨约束区域网平差模型能减少对控制点的需求,提高平差精度。     

轨道约束的资源三号标准景影像区域网平差

考虑到同轨道拍摄的长条带卫星影像具有相同的误差分布特性,针对资源三号的标准景影像产品,提出了基于轨道约束的卫星影像区域网平差方法。首先,根据同轨相邻影像的偏移量计算轨道影像坐标系下的像点坐标;其次,通过同轨每景影像的RFM重新生成轨道影像的RFM,同时生成补偿格网;然后,根据基于像方仿射变换的RFM对轨道影像进行区域网平差;最后,利用求得的轨道影像的仿射变换参数重新计算原始单景影像的仿射变换参数。利用不同地区资源三号测绘卫星影像数据的试验表明,基于轨道约束的卫星影像区域网平差（以下简称轨道平差）在稀疏控制条件下,其精度明显好于单景影像平差的精度。在6控情况下,太行山试验区达到平面2.504m高程3.117m,在渭南试验区达到了平面4.061m高程2.895m。试验结果证明了轨道平差的有效性和可行性。     

高分辨率三线阵卫星遥感影像的区域网平差算法与试验

简述高分辨率遥感卫星影像的几何定位处理过程,分析了区域网平差的必要性。结合线阵传感器的成像特点,对传感器严格几何模型、卫星轨道模型、传感器内方位误差模型进行研究,初步建立了高分辨率遥感卫星的平差数学模型。采用区域网平差方法对内方位元素和外方位元素进行解算,并利用资源三号卫星线阵影像和ALOS PRISM线阵影像进行试验。试验结果表明,对高分辨率遥感卫星线阵传感器进行区域网平差可以有效提高卫星影像的几何定位精度。     

缺少控制点的SPOT-5 HRS影像RPC模型区域网平差

从卫星遥感影像区域网平差的模型出发，利用SPOT-5影像附带的参数拟合RPC模型参数，根据RPC模型和像面的仿射变换模型建立了卫星遥感影像区域网平差的数学模型。按照所构建的数学模型。对两个地区SPOT-5HRS影像进行直接空间前方交会和缺少控制点的区域网平差处理。试验证明了本文模型的可行性。     

CBERS-02B卫星遥感影像的区域网平差

针对中巴资源一号卫星(CBERS-02B)卫星遥感影像姿态角误差较大的特点,提出了利用区域网平差方法提高其对地目标定位精度的策略和具体计算过程。首先对参与平差的每景影像选取4个地面控制点进行影像姿态角常差检校,然后采用与地形无关方案解求各自的RPC参数,最后选取带仿射变换项的有理函数模型(RFM)进行多重覆盖影像的区域网平差。对两个地区的0级CBERS-02B单条CCD立体影像对的区域网平差试验表明,对地目标定位的平面和高程精度均达到了±3个像元的水平,且高程精度明显优于平面精度。相对于常规的卫星遥感影像区域网平差方法,平面和高程精度均有明显提升,几乎达到国外同等高分辨率卫星遥感影像的几何定位精度。这说明中国卫星遥感影像亦具有较好的几何定位潜力,在区域网平差之前进行系统误差预改正是必要和可行的。     

An improved geopositioning model of QuickBird high resolution satellite imagery by compensating spatial correlated errors

A lot of studies have been done for correcting the systematic biases of high resolution satellite images (HRSI), which is a fundamental work in the geometric orientation and the geopositioning of HRSI. All the existing bias-corrected models eliminate the biases in the images by expressing the biases as a function of some deterministic parameters (i.e. shift, drift, or affine transformation models), which is indeed effective for most of the commercial high resolution satellite imagery (i.e. IKONOS, GeoEye-1, WorldView-1/2) except for QuickBird. Studies found that QuickBird is the only one that needs more than a simple shift model to absorb the strong residual systematic errors. To further improve the image geopositioning of QuickBird image, in this paper, we introduce space correlated errors (SCEs) and model them as signals in the bias-corrected rational function model (RFM) and estimate the SCEs at the ground control points (GCPs) together with the bias-corrected parameters using least squares collocation. With these estimated SCEs at GCPs, we then predict the SCEs at the unknown points according to their stochastic correlation with SCEs at the GCPs. Finally, we carry out geopositioning for these unknown points after compensating both the biases and the SCEs. The performance of our improved geopositioning model is demonstrated with a stereo pair of QuickBird cross-track images in the Shanghai urban area. The results show that the SCEs exist in HRSI and the presented geopositioning model exhibits a significant improvement, larger than 20% in both latitude and height directions and about 2.8% in longitude direction, in geopositioning accuracy compared to the common used affine transformation model (ATM), which is not taking SCEs into account. The statistical results also show that our improved geopositioning model is superior to the ATM and the second polynomial model (SPM) in both accuracy and reliability for the geopositioning of HRSI.     

Epipolar resampling of linear pushbroom satellite imagery by a new epipolarity model

This paper presents a practical epipolarity model for high-resolution linear pushbroom satellite images acquired in either along-track or cross-track mode, based on the projection reference plane in object space. A new method for epipolar resampling of satellite stereo imagery based on this model is then developed. In this method, the pixel-to-pixel relationship between the original image and the generated epipolar image is established directly by the geometric sensor model. The approximate epipolar images are generated in a manner similar to digital image rectification. In addition, by arranging the approximate epipolar lines on the defined projection reference plane, a stereoscopic model with consistent ground sampling distance and parallel to the object space is thus available, which is more convenient for three-dimensional measurement and interpretation. The results obtained from SPOT5, IKONOS, IRS-P5, and QuickBird stereo images indicate that the generated epipolar images all achieve high accuracy. Moreover, the vertical parallaxes at check points are at sub-pixel level, thus proving the feasibility, correctness, and applicability of the method.     

高分辨率遥感影像的精纠正

论述了对高分辨率遥感影像进行精纠正获得正射影像的关键技术。若干实际不同分辨率的高分辨率遥感影像被用于相应的实验，实例证明了本文算法的正确性。     

Bundle Adjustment with Self–Calibration Using Straight Lines

Increased use of digital imagery has facilitated the opportunity to use features, in addition to points, in photogrammetric applications. Straight lines are often present in object space, and prior research has focused on incorporating straight–line constraints into bundle adjustment for frame imagery. In the research reported in this paper, object–space straight lines are used in a bundle adjustment with self–calibration. The perspective projection of straight lines in the object space produces straight lines in the image space in the absence of distortions. Any deviations from straightness in the image space are attributed to various distortion sources, such as radial and decentric lens distortions. Before incorporating straight lines into a bundle adjustment with self–calibration, the representation and perspective transformation of straight lines between image space and object space should be addressed. In this investigation, images of straight lines are represented as a sequence of points along the image line. Also, two points along the object–space straight line are used to represent that line. The perspective relationship between image– and object–space lines is incorporated in a mathematical constraint. The underlying principle in this constraint is that the vector from the perspective centre to an image point on a straight–line feature lies on the plane defined by the perspective centre and the two object points defining the straight line. This constraint has been embedded in a software application for bundle adjustment with self–calibration that can incorporate point as well as straight–line features. Experiments with simulated and real data have proved the feasibility and the efficiency of the algorithm proposed.     

高分辨率光学遥感卫星在轨几何定标现状与展望

光学遥感卫星影像在轨几何定标是确保影像几何质量的必要环节。首先介绍了光学卫星在轨几何定标方法的研究现状;然后,对于当前主流的基于地面几何检校场的在轨几何定标方法,结合光学卫星地面分辨率不断提高的发展趋势,阐述了其受限于对参考影像的依赖而存在的问题;最后,论述了无需地面定标场的在轨自主几何定标的发展趋势,并提出了多种基于多角度交叉约束成像的在轨自主几何定标方法构想。     

城市绿地信息提取遥感影像尺度效应分析

绿地信息提取精度与影像的空间尺度有关,又与提取目标的特点有关。目前用于绿地信息提取的高分辨率遥感影像主要有QUICKBIRD、IKONOS和SPOT5,不同尺度影像对绿地信息提取精度的影响还缺少相关的研究。本文利用目视解译方法,研究三种尺度遥感影像提取绿地信息的精度。结果表明,三种影像中,由于QUICK-BIRD影像有更详细的空间结构,更适合于城市绿地零星分布特点,在以7层建筑物以下为主的研究区,绿地信息提取精度最高。     

An automatic mosaicking method for building facade texture mapping using a monocular close-range image sequence

This paper presents an automatic mosaicking method for generating building facade textures from a monocular close-range digital image sequence. The process begins with the computation of the camera parameters (except the coordinates of the projective center), which are determined by combining vanishing point geometry with constraints of a straight line bundle as well as prior information of parallel lines in object space. The raw images are later rectified for the purpose of eliminating their salient geometric distortion. Next, automatic retrieval of the relevant image segment is implemented using the detecting range variance by means of the histogram of projective differences between the corresponding points for each of the facades from the raw image sequence. A strip model of the least-squares adjustment, which is similar to the strip block adjustment in aerial triangulation, is employed to determine the spatial alignment of each of the image segments in order to generate the facade textures from the relevant image segments. Afterwards, the entire building facade texture is mosaicked by ortho-image generation. Two refining strategies are proposed to optimize the mosaic result. One is refining the mosaic region where corresponding points are difficult to match but plenty of horizontal lines are available, and the constraint of corresponding horizontal lines is introduced to implement this process. The other strategy is to refine the unsatisfactory mosaic region by densifying the corresponding points by means of the spatial alignment of the relevant image segment computed by the strip method. The experimental results indicate that this method is widely applicable and compares well with other reported approaches with regard to automation level and applicability, for uncalibrated images as well as images with large geometric distortions.     

利用距离变换模型进行卫星影像与激光点云精配准

卫星影像可以低成本、高频率地提供地物光谱特性观测信息,而激光点云可以提供精细的几何结构,两类数据的融合可以实现优势互补,进一步提高地物分类和信息提取的精度和自动化程度。实现亚像素级精度的几何配准是实现两类数据融合的前提,提出了一种基于线元素距离变换模型的快速配准方法。该方法以点云为控制源,将点云中的建筑物边缘等典型线元素通过卫星影像的初始有理多项式系数(rational polynomial coefficient, RPC)投影到像方空间,与卫星影像中的线元素进行迭代最近点配准,从而通过RPC参数精校正的方式实现几何配准。采用距离变换模型作为迭代最近点搜索的查找表,提高了运算效率;采用最新的渐进式鲁棒求解策略,能在噪声极多的情况下保证配准的鲁棒性。采用GeoEye-2、高分七号、WorldView-3等卫星影像与激光点云进行了配准实验,并分别通过人工精确量测的外业控制点和作业员内业刺的控制点作为检查,证明所提方法能在3种影像上达到0.4～0.7 m的配准精度,显著优于将点云映射为二维图像然后通过多模态匹配进行配准的策略。     

Precision rectification of high resolution satellite imagery without ephemeris data

The huge capability of high resolution satellite imageries (HRSI), that includes spatial, spectral, temporal and radiometric resolutions as well as stereoscopic vision introduces them as a powerful new source for the Photogrammetry, Remote Sensing and GIS communities. High resolution data increases the need for higher accuracy of data modeling. The satellite orbit, position, attitude angles and interior orientation parameters have to be adjusted in the geometrical model to achieve optimal accuracy with the use of a minimum number of Ground Control Points (GCPs). But most high resolution satellite vendors do not intend to publish their sensor models and ephemeris data. There is consequently a need for a range of alternative, practical approaches for extracting accurate 2D and 3D terrain information from HRSI. The flexibility and good accuracy of the alternative models demonstrated with KFA-1000 and the well-known SPOT level 1A images. A block of eight KFA-1000 space photos in two strips with 60% longitudinal overlap and 15% lateral sidelap and SPOT image with rational function, DLT, 2D projective, polynomials, affine, conformal, multiquadric and finite element methods were used in the test. The test areas cover parts of South and West of Iran. Considering the quality of GCPs, the best result was found with the DLT method with a RMSE of 8.44 m for the KFA-1000 space photos.