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71.
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图像匹配作为三维重建至关重要的环节,其精度直接影响了平差优化、正射校正等模块的精度。对于城镇、农场等特征密集型区域,特征距离小,相似性强,易于匹配图像;而针对草地、沙漠等特征不明显区域,特征距离大,如果使用特征点匹配的方法,严格阈值下难以获得足够数量的匹配对,放宽阈值又将引入较多误匹配对,这也是导致稀疏点云不够均匀的原因之一。在此场景下,本文提出了基于动态极坐标参数化的无人机正视影像匹配算法,首先对图像做极坐标参数变化,采用动态策略解决极轴方向采样不均匀的问题,使用最小二乘法对得到的极坐标影像对做位移方向上的匹配,匹配后得到的旋转量和平移量,将该结果和SIFT算法的结果做比较。本文设计了2组实验,即参数已知的解算实验和参数未知的解算实验,且每组实验进行3次。在同等配置的计算机上,对两张7360像素×5400像素,32位的影像,本文方法的位姿解算时间相比SIFT的时间减少约57%,二者求得的位姿差通常小于1%。结论表明二者的结果在精度上表现相当,在时间上明显优于SIFT算法,具有实际的应用价值。 相似文献
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Ayman F. Habib Ana Paula Kersting Ki-In Bang Ruifang Zhai Mohannad Al-Durgham 《The Photogrammetric Record》2009,24(126):171-195
Lidar (laser scanning) technology has been proven as a prominent technique for the acquisition of high-density and accurate topographic information. Because of systematic errors in the lidar measurements (drifts in the position and orientation information and biases in the mirror angles and ranges) and/or in the parameters relating the system components (mounting parameters), adjacent lidar strips may exhibit discrepancies. Although position and orientation drifts can have a more significant impact, these errors and their impact do not come as a surprise if the quality of the GPS/INS integration process is carefully examined. Therefore, the mounting errors are singled out in this work. The ideal solution for improving the compatibility of neighbouring strips in the presence of errors in the mounting parameters is the implementation of a rigorous calibration procedure. However, such a calibration requires the original observations, which may not be usually available. In this paper, a strip adjustment procedure to improve the compatibility between parallel lidar strips with moderate flight dynamics (for example, acquired by a fixed-wing aircraft) over an area with moderately varying elevation is proposed. The proposed method is similar to the photogrammetric block adjustment of independent models. Instead of point features, planar patches and linear features, which are represented by sets of non-conjugate points, are used for the strip adjustment. The feasibility and the performance of the proposed procedure together with its impact on subsequent activities are illustrated using experimental results from real data. 相似文献
75.
矢量图形与影像图像一体化实现 总被引：3，自引：0，他引：3
本文在阐述影像金字塔相关理论（构建方法、影像切割等）的基础上,采用VC2005编程实现了在同一GIS系统中进行矢量数据和栅格数据叠加显示的功能模块。该模块可确定是否加载影像,并根据当前矢量图显示范围自动加载不同分辨率的影像图。 相似文献
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It is well known that high-leverage observations significantly affect the estimation of parameters. In geodetic literature,
mainly redundancy numbers are used for the detection of single high-leverage observations or of single redundant observations. In this paper a further objective method for the detection of groups of important and less important (and thus redundant) observations is developed. In addition, the parameters which are predominantly
affected by these groups of observations are identified. This method thus complements other diagnostics tools, such as, e.g.,
multiple row diagnostics methods as described in statistical literature (see, e.g., Belsley et al. in Regression diagnostics:
identifying influential data and sources of collinearity. Wiley, New York, 1980). The method proposed in this paper is based
on geometric aspects of adjustment theory and uses the singular value decomposition of the design matrix of an adjustment
problem together with cluster analysis methods for regression diagnostics. It can be applied to any geodetic adjustment problem
and can be used for the detection of (groups of) observations that significantly affect the estimated parameters or that are
of negligible impact. One of the advantages of the proposed method is the improvement of the reliability of observation plans
and thus the reduction of the impact of individual observations (and outliers) on the estimated parameters. This is of particular importance for the very long baseline interferometry
technique which serves as an application example of the regression diagnostics tool. 相似文献
79.
Z. Wiśniewski 《Journal of Geodesy》2009,83(2):105-120
The paper presents a method of estimating parameters in two competitive functional models. The models considered here are
concerned with the same observation set and are based on the assumption that an observation may result from a realization
of either of two different random variables. These variables differ from one another at least in the main characteristic (for
example, outliers can be realizations of one variable). A quantity that describes the opportunity of identifying a single
observation with one random variable is assumed to be known. That quantity, called the elementary split potential, is strictly
referred to the amount of information that an observation can provide about two competitive assumptions concerning the observation
distribution. Parameter assessments that maximize the global elementary split potential (concerning all observations), are
called M
split estimators. A generalization of M
split estimation presented in the paper refers to the theoretical foundation of M-estimation.
An erratum to this article can be found at 相似文献
80.