A convergent image configuration for DEM extraction that minimises the systematic effects caused by an inaccurate lens model
A convergent image configuration for DEM extraction that minimises the systematic effects caused by an inaccurate lens model
复制标题
用于 DEM 提取的会聚图像配置，可最大限度地减少由不准确的镜头模型引起的系统影响
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
J. Chandler
中科院分区：
文献类型：
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作者：
R. Wackrow;J. Chandler
消费级数码相机的内部几何形状通常被认为是不稳定的。拉夫堡大学最近进行的研究表明，这些传感器有潜力保持其内部几何形状。它还确定了残留的系统误差表面或“圆顶”，在数字高程模型（DEM）中可辨别的，造成轻微不准确的估计透镜失真参数。本文研究了这些系统误差曲面，并建立了一种方法，以尽量减少它们。最初，模拟数据被用来确定改变提取的DEM，特别是透镜模型的内部取向参数的影响。给出的结果证明了“圆顶”和不准确指定的透镜畸变参数之间的关系。立体像对对于摄影测量中的数据提取仍然很重要，通常使用自动DEM提取软件。摄影测量中普遍采用的是摄影测量法，即摄影机底座平行于物面，摄影机光轴与物面正交。在仿真过程中，使用正常情况下提取的DEM导出的误差表面进行比较，使用温和收敛的几何形状创建的误差表面。与正常情况相比，光学相机轴在同一点处与物平面相交。仿真过程的结果清楚地表明，一个温和的收敛相机配置根除系统误差表面。这一结果通过实际测试得到了证实，并表明适度收敛的图像有效地提高了使用此类传感器获得的DEM的精度。
The internal geometry of consumer‐grade digital cameras is generally considered unstable. Research conducted recently at Loughborough University indicated the potential of these sensors to maintain their internal geometry. It also identified residual systematic error surfaces or “domes”, discernible in digital elevation models (DEMs), caused by slightly inaccurate estimated lens distortion parameters. This paper investigates these systematic error surfaces and establishes a methodology to minimise them. Initially, simulated data was used to ascertain the effect of changing the interior orientation parameters on extracted DEMs, specifically the lens model. Results presented demonstrate the relationship between “domes” and inaccurately specified lens distortion parameters. The stereopair remains important for data extraction in photogrammetry, often using automated DEM extraction software. The photogrammetric normal case is widely used, in which the camera base is parallel to the object plane and the optical axes of the cameras intersect the object plane orthogonally. During simulation, the error surfaces derived from extracted DEMs using the normal case were compared with error surfaces created using a mildly convergent geometry. In contrast to the normal case, the optical camera axes intersect the object plane at the same point. Results of the simulation process clearly demonstrate that a mildly convergent camera configuration eradicates the systematic error surfaces. This result was confirmed through practical tests and demonstrates that mildly convergent imagery effectively improves the accuracies of DEMs derived with this class of sensor.