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Reconstruction of a conic-section surface from autocollimator-based deflectometric profilometry

机译:基于自准直仪的折光轮廓仪重建圆锥形截面表面

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We present a description of our method to process a set of autocollimator-based deflectometer one-dimensional line scans taken over a large optical surface and reconstruct them to a best-fit conic-section surface. The challenge with our task is that each line scan is in a different (unknown) coordinate reference frame with respect to the other line scans in the set. This problem arises due to the limited angular measurement range of the autocollimator used in the deflectometer and the need to measure over a greater range. This results in the optic under measurement being rotated (in pitch and roll) between each scan to bring the autocollimator back into measurement range and therefore each scan is taken in a different coordinate frame. We describe an approach using a 6N + 2 dimension optimization (where N is the number of scan lines taken across the mirror) that uses a gradient-based nonlinear least squares fitting combined with a multistart global-search strategy to find the best-fit surface. Careful formulation of the problem is required to reduce numerical noise and allow the routine to converge on a solution of the required accuracy. (C) 2016 Optical Society of America
机译:我们介绍了一种方法的描述,该方法用于处理在大光学表面上进行的一组基于自动准直器的偏转仪一维线扫描,并将其重建为最适合的圆锥截面表面。我们任务的挑战在于,相对于集合中的其他线扫描,每个线扫描都在不同的(未知)坐标参考系中。由于在偏转仪中使用的自动准直仪的角度测量范围有限,并且需要在更大范围内进行测量,因此会出现此问题。这导致被测光学器件在每次扫描之间旋转(俯仰和滚动),以使自动准直仪回到测量范围,因此每次扫描都在不同的坐标系中进行。我们描述了一种使用6N + 2维优化的方法(其中N是横穿镜子的扫描线的数量),该方法将基于梯度的非线性最小二乘拟合与多起点全局搜索策略相结合,以找到最适合的曲面。需要仔细地解决问题,以减少数值噪声,并使例程收敛于所需精度的解决方案上。 (C)2016美国眼镜学会

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