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A novel 3D stitching method for WLI based large range surface topography measurement

机译:基于WLI的大范围表面形貌测量的新型3D拼接方法

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摘要

3D image stitching is an important technique for large range surface topography measurement in White-Eight Interferometry (WEI). However, the stitching accuracy is inevitably influenced by noise. To solve this problem, a novel method for 3D image stitching is proposed in this paper. In this method, based on noise mechanism analysis in WEI measurement, a new definition of noise in 3D image is given by an evaluation model for difference between the practical WEI interference signal and the ideal signal. By this new definition, actual noises in 3D image are identified while those practical singular heights on surface will not be wrongly attributed to noise. With the definition, a binary matrix for noise mark corresponding Lo 3D image is obtained. Then, the matrix is devoted, as an important component, to establish a series of new algorithms of capability for suppressing the adverse effects of noises in each process of the proposed stitching method. By this method, the influence of the noises on stitching is substantially reduced and the stitching accuracy is improved. Through 3D image stitching experiments with noises in WLE effectiveness of the proposed method is verified. (C) 2015 Elsevier B.V. All rights reserved.
机译:3D图像拼接是白干涉法(WEI)中大范围表面形貌测量的一项重要技术。但是,拼接精度不可避免地受到噪声的影响。为了解决这个问题,本文提出了一种新颖的3D图像拼接方法。在这种方法中,基于WEI测量中的噪声机制分析,通过评估模型对实际WEI干扰信号与理想信号之间的差异给出了3D图像中噪声的新定义。通过这个新定义,可以识别3D图像中的实际噪声,而不会将表面上的那些实际奇异高度错误地归因于噪声。通过该定义,获得了用于噪声标记对应的Lo 3D图像的二进制矩阵。然后,将矩阵作为重要组成部分,以建立一系列新的算法来抑制所提出的缝合方法的每个过程中噪声的不利影响。通过这种方法,基本上减少了噪声对缝合的影响,并且提高了缝合精度。通过在噪声中进行3D图像拼接实验,验证了该方法的有效性。 (C)2015 Elsevier B.V.保留所有权利。

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